Open Access

Transcriptomic and metabolite analyses of Cabernet Sauvignon grape berry development

  • Laurent G Deluc1,
  • Jérôme Grimplet1,
  • Matthew D Wheatley1,
  • Richard L Tillett1,
  • David R Quilici1,
  • Craig Osborne2,
  • David A Schooley1,
  • Karen A Schlauch3,
  • John C Cushman1 and
  • Grant R Cramer1Email author
BMC Genomics20078:429

DOI: 10.1186/1471-2164-8-429

Received: 14 May 2007

Accepted: 22 November 2007

Published: 22 November 2007

Abstract

Background

Grape berry development is a dynamic process that involves a complex series of molecular genetic and biochemical changes divided into three major phases. During initial berry growth (Phase I), berry size increases along a sigmoidal growth curve due to cell division and subsequent cell expansion, and organic acids (mainly malate and tartrate), tannins, and hydroxycinnamates accumulate to peak levels. The second major phase (Phase II) is defined as a lag phase in which cell expansion ceases and sugars begin to accumulate. Véraison (the onset of ripening) marks the beginning of the third major phase (Phase III) in which berries undergo a second period of sigmoidal growth due to additional mesocarp cell expansion, accumulation of anthocyanin pigments for berry color, accumulation of volatile compounds for aroma, softening, peak accumulation of sugars (mainly glucose and fructose), and a decline in organic acid accumulation. In order to understand the transcriptional network responsible for controlling berry development, mRNA expression profiling was conducted on berries of V. vinifera Cabernet Sauvignon using the Affymetrix GeneChip® Vitis oligonucleotide microarray ver. 1.0 spanning seven stages of berry development from small pea size berries (E-L stages 31 to 33 as defined by the modified E-L system), through véraison (E-L stages 34 and 35), to mature berries (E-L stages 36 and 38). Selected metabolites were profiled in parallel with mRNA expression profiling to understand the effect of transcriptional regulatory processes on specific metabolite production that ultimately influence the organoleptic properties of wine.

Results

Over the course of berry development whole fruit tissues were found to express an average of 74.5% of probes represented on the Vitis microarray, which has 14,470 Unigenes. Approximately 60% of the expressed transcripts were differentially expressed between at least two out of the seven stages of berry development (28% of transcripts, 4,151 Unigenes, had pronounced (≥2 fold) differences in mRNA expression) illustrating the dynamic nature of the developmental process. The subset of 4,151 Unigenes was split into twenty well-correlated expression profiles. Expression profile patterns included those with declining or increasing mRNA expression over the course of berry development as well as transient peak or trough patterns across various developmental stages as defined by the modified E-L system. These detailed surveys revealed the expression patterns for genes that play key functional roles in phytohormone biosynthesis and response, calcium sequestration, transport and signaling, cell wall metabolism mediating expansion, ripening, and softening, flavonoid metabolism and transport, organic and amino acid metabolism, hexose sugar and triose phosphate metabolism and transport, starch metabolism, photosynthesis, circadian cycles and pathogen resistance. In particular, mRNA expression patterns of transcription factors, abscisic acid (ABA) biosynthesis, and calcium signaling genes identified candidate factors likely to participate in the progression of key developmental events such as véraison and potential candidate genes associated with such processes as auxin partitioning within berry cells, aroma compound production, and pathway regulation and sequestration of flavonoid compounds. Finally, analysis of sugar metabolism gene expression patterns indicated the existence of an alternative pathway for glucose and triose phosphate production that is invoked from véraison to mature berries.

Conclusion

These results reveal the first high-resolution picture of the transcriptome dynamics that occur during seven stages of grape berry development. This work also establishes an extensive catalog of gene expression patterns for future investigations aimed at the dissection of the transcriptional regulatory hierarchies that govern berry development in a widely grown cultivar of wine grape. More importantly, this analysis identified a set of previously unknown genes potentially involved in critical steps associated with fruit development that can now be subjected to functional testing.

Background

Grapes have been cultivated and fermented into wine for more than 7,000 years. Worldwide, grapes are one of the most widely cultivated fruit crops, encompassing 7.4 million hectares of arable land in 2006 [1] and with 68.9 million metric tons produced in 2006, ranks second among bananas, oranges, and apples with 69.7, 63.8 and 62.1 million metric tons respectively, produced during this same period. However, because the majority of the grapes that are harvested are fermented into wine, the economic impact for this commodity is far greater than the value of the grapes. For example, wine sales from California alone in 2006 was at an all-time high and growing with approximately $18 billion dollar in sales [2]. According to 2005 statistics, the California wine industry has a $52 and $125 billion economic impact on the state and U.S. economies, respectively [3].

In addition to their economic importance, consumption of grapes and wine has numerous nutritional and health benefits for humans [4, 5]. For example, there are more than 200 polyphenolic compounds in red wines that are thought to act as antioxidants. In particular, one antioxidant compound, trans-resveratrol, has been shown to play a role in the prevention of heart disease (atherosclerosis) [6] and cancer [7]. Resveratrol slows the aging process in animals [8], acts as a signaling molecule in the brain [9], and down-regulates the expression of genes that are involved in cell cycle and cell proliferation in human prostate cells [10]. Therefore, for a variety of reasons, there is great interest in manipulating grape berry development and quality for both economic and health reasons.

In contrast to the well studied climacteric fruits such as tomato and apple, very little is known about the development and ripening processes of non-climacteric fruits such as grape or strawberry [11, 12]. In 1992, Coombe, one of the leaders in the field, described our knowledge of grape berry development and the regulation of ripening as "embryonic [13]."

Grape berries, like other berry fruits, undergo a complex series of physical and biochemical changes during development, which can be divided into three major phases [13] with more detailed descriptive designations, known as the modified E-L system, being used to define more precise growth stages over the entire grapevine lifecycle [14]. During the initial stage of berry growth (Phase I) cell division is rapid and all cells are established in the developing fruit in the first two weeks after flowering followed by a subsequent sigmoidal increase in berry size over approximately 60 days due to cell expansion. Two important organic acids, tartrate and malate, are synthesized and reach maximal concentrations by the end of Phase I. Biosynthesis of tannins and hydroxycinnamates, which are major precursors for phenolic volatiles, also occurs, primarily during Phase I. Tannins are located primarily in the skin and seeds of the berry, and are perceived as astringent compounds important for color stability and the body of red wine.

Phase II is characterized as a lag phase during which there is no increase in berry size. Biosynthetic processes are not well characterized for this stage, but it is known that sugar accumulation begins during this phase just prior to véraison (the onset of ripening) [13]. Véraison marks the start of Phase III of berry growth, which is characterized by the initiation of color development (anthocyanin accumulation in red grapes) and berry softening. Berry growth is sigmoidal during Phase III, as the berries double in size. At the onset of this stage, sugars (largely glucose and fructose) continue to accumulate, and organic acid concentrations decline. The acid:sugar balance at harvest is critical for high quality wines, as it affects important sensory attributes [15]. A large number of the flavor compounds and volatile aromas are synthesized at the end of Stage III. Many of these aromas are derived from terpenoids. However, the availability of seed tannins declines through oxidative processes during Phase III, causing the tannins to bind to the seed coat, reducing the astringent components within the berry. Skin tannins begin to interact and bind with anthocyanins and each other, increasing tannin polymer size and complexity.

Two major objectives of modern viticultural practices include the ability to produce a uniformly ripe crop and to harvest at optimal grape maturity. Large variations in ripening among berries within a cluster and within a vineyard make it difficult to determine when a crop is at its best possible ripeness. The start of véraison is recognized to be a critical determinant for berry harvest dates, yet little is known about what initiates this important stage. A more detailed understanding of the complex changes in gene expression that orchestrate berry developmental processes is needed.

Several mRNA expression-profiling studies have been completed for Vitis berries. Differential screening of cDNA libraries from (Vitis vinifera cv. Shiraz) and northern blot analysis revealed that large differences in gene expression occur during berry ripening and led to the isolation of a large number of grape ripening-induced protein (GRIP) genes [16]. Monitoring of gene expression profiles in flowers and across six time points during grape (Vitis vinifera cv. Shiraz) berry skin development to 13 weeks post-flowering resolved four sets of genes with distinctive and similar expression patterns using spotted cDNA microarrays containing 4,608 elements [17]. mRNA expression was also studied across nine stages of wildtype cv. Shiraz berry development (green "pea" to overripe) [18] and in a fleshless berry mutant cv. Ugni Blanc using oligonucleotide microarrays containing 3,200 elements [19]. Differences in transcript expression profiles in the skin of ripening fruit (12 to 13 weeks after flowering) of seven different cultivars were also examined using a 9,200 feature cDNA microarray [20]. In this study, we conducted mRNA expression profiling on one of the widely grown varieties of V. vinifera (cv Cabernet Sauvignon) using the Vitis Affymetrix GeneChip® oligonucleotide microarray ver. 1.0, which contains 14,470 Unigenes, over seven temporal stages (green "pea" to ripe) of berry development. We also correlated specific transcript profiles with specific metabolite profiles to gain deeper insights into discrete aspects of grape berry developmental dynamics.

Results and discussion

Grape berry development

Vitis vinifera cv. Cabernet Sauvignon grapes were harvested on a weekly basis over the course of berry development from the Shenandoah Vineyard, Plymouth, California during the summer of 2004. Samples corresponding to stages 31 to 38 of the modified E-L system [14] were measured for berry diameter, °Brix (an approximate measure of the mass ratio of dissolved solids, mostly sucrose, to water in fruit juices) and titratable acidity (Figure 1). Berry diameter increased over time with a classical double sigmoid pattern (Figure 1A). Average berry diameter increased during the first 7 weeks of development (E-L stage 31), followed by a cessation of berry expansion at 7 to 8 weeks post-anthesis (E-L stages 32 to 34), and then the increase in berry diameter resumed until maturity (E-L stages 35 to 38). °Brix increased 6 weeks post-anthesis to a peak value of 22 °Brix at 16 weeks post-anthesis (Figure 1B). In contrast, titratable acidity (g/L), which reflects acid accumulation (mainly tartaric and malic acid), increased steadily up to 8 weeks post-anthesis and then sharply declined at the start of véraison between E-L stages 34 and 35 reaching approximately 7 g/L of titratable acids at harvest (Figure 1C).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-429/MediaObjects/12864_2007_Article_1142_Fig1_HTML.jpg
Figure 1

Physiological data at different stages of berry development. Changes in physiological parameters measured during the major phases (I to III) of berry development and ripening of Cabernet Sauvignon grape berries. A, Berry Diameter (n = 6); B, Brix degree (°) or total soluble solids in the berry juice (n = 6); C, Titratable Acidity (g/L) (n = 6). The stage at which véraison occurs is indicated in pink. Numbers with arrows point to the individual developmental stages defined by the E-L system Coombe [14] used for transcriptome profiling.

Microarray analysis

The mRNA expression profiles of seven time points spanning E-L stages 31 to 38 as indicated in Figure 1 were compared using the Affymetrix GeneChip® Vitis genome array ver. 1.0. Testing was performed using biological triplicates for each time point. Multiple time points within Stage II (E-L stages 32 to 35) were sampled due to the large number of biochemical changes expected to occur around véraison that affect berry ripening and fruit quality. A visual inspection of the distributions of raw perfect match (PM) probe-level intensities for all 21 arrays showed that the pre-processed and normalized PM intensities using Robust Multi-Array Average (RMA) [21] were consistent across all arrays. Digestion curves describing trends in RNA degradation between the 5' end and the 3' end in each probe set were examined and all 21 proved very similar [Additional File 1A,B]. Correlations among biological replicates were good: Spearman coefficients ranged from 0.977 to 0.997; Pearson coefficients ranged between 0.977 and 0.996.

From the Vitis 16,602 probesets represented on the array [Additional File 1C], an overall mean call rate of 74.5% per array (range 73.5% to 76.2%) was obtained. Data from the 12,596 probe sets that were found to be present in at least two out of the three biological triplicates were retained for further analyses. After performing an ANOVA and a multiple testing correction (Benjamini and Hochberg) [22], we found that 10,068 probesets (60.6%) were differentially expressed (p ≤ 0.05) between two or more E-L stages of berry development [Additional File 2: Table 1]. Because one Unigene can be related to several probesets, the number of Unigenes decreased to 9,143 Unigenes [Additional File 2: Table 2]. These probesets will be hereby referred to as those passing the ANOVA filter. From this set of genes, we extracted a subset of 4,510 probesets that displayed a two-fold or greater change in steady-state transcript abundance over the course of development (i.e., across any two of the seven developmental stages) [Additional File 2: Table 3] representing 4,151 Unigenes (28.3%) in the DFCI Grape Gene Index database VvGI5 [23]. We refer to this subset of genes as the two-fold ratio (TFR) set [Additional File 2: Table 4].

Principal component analysis (PCA), was used to simplify and define associations between different developmental stages within the global transcriptomic data (Additional File 3). Two principal components explaining 97.4% of the overall variance of transcription profiles (86.8% and 7.6% for axes 1 and 2, respectively) allowed us to clearly differentiate E-L stages 31 and 35 from the other developmental stages analyzed (Additional File 3). It was not possible to clearly separate E-L stages 32 to 34 or 36 to 38 indicating that the transcription patterns occurring at these stages were similar to one another. However, stage 35, which corresponds to early post-véraison, could be distinguished suggesting that transcription patterns at this point in berry ripening are unique to this critical stage in berry development. Further analysis using a third axis explaining 2.7% of the overall variance, confirmed the previous results and slightly improved the resolution among stages 31, 35, and 36 to 38.

Clustering of significant genes

We used the Pavlidis Template Matching (PTM) algorithm [24], to divide the 4,151 TFR Unigenes into twenty gene groups or clusters. Specifically, twenty gene profiles of interest were selected [Additional File 4] to reflect major transcriptional patterns of development across E-L stages 31 to 38 (Figure 2). The PTM algorithm then classified the gene profiles into twenty groups via measurements of Pearson correlation: a correlation coefficient of greater than 0.75 was used to determine cluster membership. Six profiles showed a steady decline (profile groups 1 to 3) or increase (profile groups 9 to 11) in steady-state transcript abundance over time with distinctly different slopes. These six profile groups encompassed 63% of the Unigenes with a majority expressed in profiles 2 and 3 (31.9%) and profiles 9 and 11 (28%; Figure 2). Eight profiles had transient peak increases (profile groups 4 to 8) or decreases (profile groups 12 to 16) in transcript abundance at each of E-L stages 32 to 36. These transient profiles accounted for 22% of the Unigenes. A majority (68.2%) of these transiently expressed genes (profile groups 4 to 8 and 12 to 16) exhibited increased transcript abundance with the highest proportion within profile group 16 (E-L stage 36), followed closely by profile group 15 (E-L stage 35 around véraison), and profile group 12 (E-L stage 32) (Figure 2). Interestingly, genes with transient decreases early in berry development (profile groups 4 and 5) also exhibited large increases in transcript abundance during the later stages (E-L stages 36 to 38). The last four profiles (profile groups 17–20) were selected as having two peaks of expression between E-L stages 32 and 36 (Figure 2). Approximately 4.3% of transcripts had such "up and down" expression patterns (profile groups 17–20). Finally, Unigenes that did not match one of these profiles were grouped into a 21st cluster (Figure 2), accounting for 11% of the total transcripts considered (profile group 21). Taken together, this analysis revealed that berry development is not only a progressive process, wherein the majority of genes exhibit a steady increase or decrease in expression across all stages of development (profile groups 1 to 3 and 9 to 11), but also a dynamic process, wherein a large number of genes exhibit large, transient changes in transcript abundance at specific times of development. Most notably, the last phase of berry development (Phase III, profile groups 14, 15 and 16) was the time when the largest number of genes (380 transcripts or 9.1%) exhibited transient increases in steady-state transcript abundance.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-429/MediaObjects/12864_2007_Article_1142_Fig2_HTML.jpg
Figure 2

Twenty-one profiles of steady-state transcripts exhibiting a two-fold or greater expression across berry development. Profiles are plotted as RMA data values plotted on the log2 scale centered by the mean of all values (Stage 31 to stage 38). E-L Stages are indicated along the X-axis. Profiles numbers are indicated with red numbers with the number of transcripts within each profile indicated with black numbers: Véraison (V) is indicated with a pink stripe. The gradient red to green coloration of individual gene plots indicates values above or below the mean of the cluster, respectively. The cluster template profile is designated by a yellow line.

Functional categorization of Unigenes across different stages of development

Functional categories were assigned to Unigenes with two-fold or greater changes in steady-state transcript abundance over the course of the seven developmental stages using the Munich Information Center for Protein Sequences (MIPS, ver. 2.0) catalog with annotations of the top Arabidopsis BLAST hits [25]. Because we detected some errors in the functional annotation for some Unigenes, functional categorization of each Unigene were verified manually and corrected if necessary. Corrections were only performed for the 4,151 Unigenes that displayed a two-fold or greater change in expression [See Additional File 2: Table 4]. Functional annotations could be assigned to approximately 64% of transcripts (Figure 3A). An additional 23% of Unigenes had matches to genes with unknown functions or unclear classifications (unclassified), and 13% did not have a BLAST hit (no hit) in public, non-redundant (NR) databases. The relative distribution of Unigenes within each of nineteen functional categories was determined (Figure 3B). To facilitate a functional comparison of the three major stages of berry development, Unigenes from each of the profile groups were regrouped into the three major developmental phases to reflect the greatest degree of transcript abundance changes at each phase: Phase I (profiles 1, 2, and 3), Phase II (profiles 4, 5, 6, 12, 13, and 14), and Phase III (profiles 7, 8, 9, 10, 11, 15, and 16). Statistically significant differences in the distribution of genes within functional categories amongst these developmental stages were observed (Figure 3B; see Additional File 5: Tables 1 and 2). Functional categories that had a large number of transcripts in Phase I followed by a decrease in Phase III included biogenesis of cellular component (42), transport regulation (20), energy (2), and metabolism (1). This is consistent with the developmental aspects of this phase, which are characterized by cell division and expansion, which require a high level of metabolic activity. The process of cell division requires large quantities of structural materials and consumes energy, while cell expansion requires large quantities of solutes and water.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-429/MediaObjects/12864_2007_Article_1142_Fig3_HTML.jpg
Figure 3

Functional analyses of steady-state transcripts with a two-fold or greater change in abundance over the course of berry development. A) Percentage of annotated unigenes with a two-fold or greater change in transcript abundance. B) Distribution of Unigenes according to their MIPS functional categories (MIPS 2.0) within the three main phases of berry development. Phase I (E-L stage 31), herbaceous phase; Phase II (E-L stages 32 to 34), lag phase; Phase III (E-L stages 35 to 38), ripening phase. Statistically significant differences between Phase I against II are indicated with white squares. Statistically significant differences between Phase II against III are indicated with black squares. Statistically significant differences between Phase I against III are indicated with asterisks. Percentages are based upon the number of Unigenes in each set. Numbers in parentheses following category names indicates the MIPS number for each category.

The opposite trend of increasing transcript abundance from Phase I to Phase III was observed for functional groups that included transcription (11), protein synthesis (12), protein fate (14), protein with binding function (16), and to a lesser extent with interaction with cellular environment (34). These trends served to further indicate the complexity of the transcriptional, translational, and interaction-based regulatory processes necessary for berry development.

Exemplar Unigenes associated with important molecular events of berry development

In order to identify genes with potentially important roles in specific stages of berry development, transcripts with a dynamic pattern were identified from within the first 20 PTM algorithm-defined profile groups. The transcript profiles were examined in further detail (Figure 4).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-429/MediaObjects/12864_2007_Article_1142_Fig4_HTML.jpg
Figure 4

Transcripts displaying transient expression patterns. Each value plotted is the mean normalized intensity values obtained for the three biological replicates. The three key phases of the berry development (I, II, III) were applied as reference. A) Black solid round (1618814_at, NP864096)-ornithine decarboxylase, red solid triangle (1616399_s_at, CB005833)-arginine decarboxylase, green solid triangle (1611257_a_at, TC51832)-L-asparaginase, blue solid diamond (1618848_at, TC52577)-xyloglucan endotransglycosylase transferase. B) Black solid round (1608074_s_at, TC62965)-α-expansin, red solid triangle (1608191_at, TC64448) α-expansin, green solid triangle (1613161_at, TC69794)-limonene cyclase, blue solid diamond (1618595_at, TC53841)-(-)-isopiperitenol dehydrogenase.

Polyamines (PAs) are a class of compounds that have plant growth regulator activity. Their roles in cell division [26] and fruit set [27] have been widely investigated. Free, conjugated and wall-bound forms of polyamines accumulate mostly at anthesis before decreasing at fruit set in grapes [28]. Two transcripts were detected that belong to profile 4, which are strongly down-regulated at E-L stage 32 (1618814_at, 1616399_s_at; AY174164, TC68466). Both are related to ornithine decarboxylase and arginine decarboxylase, which are involved in polyamine metabolism [29]. These two genes located at the start of the PA pathway might play a role in providing precursors that would be used during Phase I of berry development.

In higher plants, the catabolism of asparagine (Asn) occurs by two routes. The first pathway involves the hydrolysis of Asn, releasing ammonia and aspartate by asparaginase activity. L-asparaginase is one of the enzymes for Asn utilization by plants that plays an important role in the nitrogen metabolism of developing plant tissues [30]. One Unigene encoding L-asparaginase (1611257_a_at; TC51832) displayed a specific peak during E-L stages 32 (Figure 4A). This last result indicates that this enzyme could play a role during the first phase of berry development as a provider of ammonia for de novo protein synthesis in grape. This result is also supported by the significant transcript abundance of Unigenes encoding glutamate dehydrogenase or glutamine synthetase (data not shown, see Additional File 2: Table 4, 1607579_at, 1613697_at, 1609819_s_at) during the first phase of berry development. These enzymes participate in nitrogen assimilation in plants [31].

In grape berries, fruit softening occurs during Phase III and is largely affected by cell-wall loosening [32] and turgor [33]. Xyloglucans account for about 10% of the cell wall composition in berries [32]. In fruit, xyloglucan depolymerization is associated with fruit softening [34]. Xyloglucan endotransglycosylases, which hydrolyze and transglycosylate xyloglucans, were encoded by multiple isogenes, the majority of which were expressed highly during Phase I in berry development (E-L stage 31), but then declined (data not shown; see Table 1). One Unigene (1618848_at; TC52577), however, which is a xyloglucan endotransglucosylase/hydrolase, displayed a 185-fold increase in expression during Phase II, peaking at E-L stage 33 (Figure 4A). This xyloglucan endotransglucosylase Unigene is closely related to a xyloglucan endotransglucosylase/hydrolase (SIXTH5) that can act reversibly. It has been characterized recently as a tomato xyloglucan depolymerase in vitro in the presence of xyloglucan oligosaccharides (XGOs) [35].
Table 1

Transcripts (TFR pool) related cell wall metabolism categorized by the first hit in the MIPS2 catalog

Probeset ID

GenBank Annotation

VvGI5

UniProt ID

Gene Name Description

Function

Profile

Fold Change

1622791_at

CB973455

TC56114

Q6J8X2

Cellulose synthase

Cell Wall Biosynthesis

2

112.68

1619280_at

CF211860

TC59569

Q6J8W9

Cellulose synthase

Cell Wall Biosynthesis

2

87.25

1613018_at

CB971117

TC61561

Q851L8

Cellulose synthase

Cell Wall Biosynthesis

2

6.92

1606646_at

CA812296

TC56773

Q6XZC2

Cellulose synthase

Cell Wall Biosynthesis

2

4.34

1615577_at

CB340193

TC52068

Q6XP46

Cellulose synthase

Cell Wall Biosynthesis

3

3.5

1607069_at

CB982496

TC53451

Q45KQ0

Cellulose synthase

Cell Wall Biosynthesis

10

3.18

1611149_at

BM437543

TC56091

Q3Y6V1

Cellulose synthase

Cell Wall Biosynthesis

21

2.85

1612999_at

CF513786

-

O80890

Cellulose synthase

Cell Wall Biosynthesis

7

2.76

1620206_at

CF515519

TC66132

Q6FD0

β 1,4-Mannan synthase

Cell Wall Biosynthesis

15

2.69

1616808_at

CF207742

TC57597

Q45KQ0

Cellulose synthase

Cell Wall Biosynthesis

21

2.21

1619938_at

CF514664

TC63356

Q6YBV2

Cellulose synthase

Cell Wall Biosynthesis

3

2.19

1620840_at

CB968965

TC53122

Q4F8K2

α-expansin

Cell Wall Expansion

2

20.26

1619010_s_at

BQ794765

TC54832

Q84US9

Expansin

Cell Wall Expansion

10

18.54

1608191_at

CD798831

TC64448

Q49QW6

Expansin

Cell Wall Expansion

21

13.18

1612253_at

CB970527

TC62108

Q6RX68

Expansin

Cell Wall Expansion

3

9.23

1608074_s_at

CF215793

TC62965

Q84UT0

Expansin

Cell Wall Expansion

21

6.28

1610418_at

BQ798078

TC67284

Q8GZD3

Expansin

Cell Wall Expansion

10

4.9

1613527_at

CB978490

TC53065

Q6T5H5

Expansin

Cell Wall Expansion

15

4.6

1618121_at

CF213691

-

Q9LUI1

Extensin

Cell Wall Expansion

2

4.1

1608504_at

BQ797231

TC52168

Q6K4C6

Expansin

Cell Wall Expansion

4

2.56

1612154_at

CB970048

TC61667

O50044

KDO 8-P synthase

Cell Wall Expansion

3

2.31

1609651_at

CF404678

TC55463

Q9LJX2

Pectinesterase inhibitor

Cell Wall Modification

2

690.87

1618848_at

CB977336

TC52577

Q9ZRV1

Xyloglucan endotransglycosylase 1

Cell Wall Modification

13

184.42

1622288_at

CB974798

TC59058

Q9M660

Cell-Wall P4

Cell Wall Modification

2

124.19

1617556_s_at

BQ797260

TC67257

Q9M4I1

Proline-rich cell wall protein

Cell Wall Modification

10

105.38

1619762_at

CF214586

TC67718

Q7Y250

Arabinogalactan protein

Cell Wall Modification

2

61.79

1620201_at

CB972625

TC70982

Q53WM8

Pectinesterase

Cell Wall Modification

2

42.57

1619519_at

CB971445

TC65487

Q7Y250

Arabinogalactan protein

Cell Wall Modification

2

39.53

1616045_a_at

AJ237983

-

Q9M4I0

Proline-rich cell wall protein

Cell Wall Modification

11

38.03

1617023_at

CF210510

TC53552

FLA1

Arabinogalactan protein

Cell Wall Modification

3

37.53

1611601_at

CB977009

TC57247

Q6ZDX2

Pectinesterase

Cell Wall Modification

2

34.83

1619613_at

CD801720

TC68597

Q9SAP3

Proline-rich protein

Cell Wall Modification

2

34.56

1616528_s_at

CD801342

TC55188

Q1SAY6

Proline-rich protein

Cell Wall Modification

2

33.73

1621880_s_at

CK138206

TC66098

Q8VZG5

β-xylosidase

Cell Wall Modification

3

31.38

1608727_at

CB973483

TC56396

Q9LZX4

Fasciclin arabinogalactan protein 10

Cell Wall Modification

3

30.04

1615533_s_at

CF415374

TC51824

Q7Y252

Endo-xyloglucan transferase

Cell Wall Modification

3

27.95

1622481_x_at

CF568921

TC67150

Q39763

Proline-rich protein

Cell Wall Modification

1

27.63

1614426_at

CD801116

TC64184

Q4F8J3

Xyloglucan endotransglycosylase

Cell Wall Modification

3

25.94

1619522_at

AY043231

TC56838

Q94B17

β-galactosidase

Cell Wall Modification

3

24.53

1622292_at

CF403386

TC69174

Q949Z1

polygalacturonase

Cell Wall Modification

2

24.24

1622295_at

CF215662

TC68541

Q5CCP8

β-galactosidase

Cell Wall Modification

3

24.1

1621477_s_at

CF215974

TC67884

Q9LYT5

Pectinesterase

Cell Wall Modification

1

23.62

1622121_at

BQ799039

TC58094

Q4F8J0

Cellulase

Cell Wall Modification

3

22.85

1615201_at

CF512517

TC63907

Q96232

Proline-rich-like protein

Cell Wall Modification

3

22.42

1618657_at

CF211626

TC56055

Q84LI7

Exopolygalacturonase

Cell Wall Modification

2

20.99

1616158_at

CD801717

TC53176

Q4JLV6

Pectate lyase

Cell Wall Modification

21

20.15

1612239_at

CF610039

TC55421

Q8VZG5

β-xylosidase

Cell Wall Modification

2

19.96

1620140_at

CF208989

TC53499

Q40161

Polygalacturonase

Cell Wall Modification

2

19.6

1611747_at

CF608890

TC65113

Q7XAS3

β-D-glucosidase

Cell Wall Modification

3

17.94

1609909_s_at

CF206328

TC64184

Q4F8J3

Xyloglucan Endotransglycosylase

Cell Wall Modification

3

15.14

1608313_at

CF209144

TC52275

Q76MS4

β-xylosidase

Cell Wall Modification

2

14.41

1615574_at

CB977067

TC56317

Q9M5J0

Pectinesterase

Cell Wall Modification

1

14.03

1619612_at

CF211611

TC67414

Q94KD8

β-xylosidase

Cell Wall Modification

2

13.83

1610073_at

CF206157

TC51796

Q8S902

Xyloglucan Endotransglycosylase

Cell Wall Modification

3

13.77

1621251_s_at

BQ795002

TC69305

Q8W3L8

Xyloglucan Endotransglycosylase 2

Cell Wall Modification

10

13.64

1622735_s_at

CB340122

TC51796

Q84JX3

Xyloglucan Endotransglycosylase

Cell Wall Modification

3

13.47

1613844_at

CF404099

TC54968

Q9LUG8

Endo-1,3-1,4-β-D-glucanase

Cell Wall Modification

3

13.27

1617755_at

CF213513

TC52924

Q8GSQ4

Pectin-glucuronyltransferase

Cell Wall Modification

2

12.86

1615746_at

CB970034

TC53433

Q9FXI9

Endo-1,4-β-glucanase

Cell Wall Modification

3

11.99

1617785_at

CD800122

TC54681

Q9LW90

Pectinesterase

Cell Wall Modification

3

11.97

1607374_at

CF404162

TC69448

Q7XAS3

β-D-glucosidase

Cell Wall Modification

3

11.77

1610311_at

CF373485

TC52429

Q41725

Arabinogalactan protein

Cell Wall Modification

3

10.99

1620096_at

CF372841

TC57673

Q4F986

Xyloglucan endotransglycosylase

Cell Wall Modification

2

10.81

1616093_at

CF404665

TC69415

Q7XA92

Pectinesterase

Cell Wall Modification

3

10.36

1613467_at

CF212805

TC54247

Q9FSW6

Arabinogalactan protein

Cell Wall Modification

15

10.08

1617875_at

CB971740

TC61493

O04477

β-N-acetylhexosaminidase

Cell Wall Modification

3

9.73

1614803_at

AY046416

TC70108

Q8LGR6

Proline-rich protein

Cell Wall Modification

3

9.22

1616822_at

AF220196

TC70108

Q8LGR6

Proline rich protein

Cell Wall Modification

3

9.04

1610756_at

CF604824

TC55088

Q9LT39

Polygalacturonase inhibitor

Cell Wall Modification

1

8.2

1622591_at

CB981129

TC70200

Q9FHN6

Pectinesterase

Cell Wall Modification

2

8.06

1612672_at

CF215975

TC62593

Q9SEE7

Pectinesterase

Cell Wall Modification

2

7.61

1616522_at

CF403905

TC55346

Q9LEB0

Pectinesterase

Cell Wall Modification

2

7.51

1615198_at

CF209943

TC65883

Q9LEC9

β-xylosidase

Cell Wall Modification

3

7.48

1608756_at

BQ798436

TC59719

Q84LI7

Polygalacturonase

Cell Wall Modification

2

7.15

1609790_at

CF207994

TC55069

Q4F8J3

Xyloglucan endotransglycosylase

Cell Wall Modification

2

6.87

1614877_at

CB002982

TC66230

Q9C8T5

Proline-rich protein

Cell Wall Modification

2

6.78

1613330_at

CF404655

-

Q93Z77

Pectate lyase

Cell Wall Modification

3

6.64

1608120_at

CF603941

TC70545

Q6U6I9

Pectate lyase

Cell Wall Modification

2

6.6

1613677_at

CB969707

TC51953

Q6J192

Arabinogalactan protein

Cell Wall Modification

2

6.16

1619383_s_at

BQ794831

TC66587

Q5CCQ0

β-galactosidase

Cell Wall Modification

3

6.14

1615603_at

CB346190

TC64570

Q8VY93

Proline-rich protein

Cell Wall Modification

3

5.75

1608180_at

CF201469

TC68224

O23950

Endo-xyloglucan transferase

Cell Wall Modification

2

5.51

1609593_at

CB981468

TC68226

Q9LZV3

(1-4)-β-mannan endohydrolase

Cell Wall Modification

15

5.49

1621225_at

CB974537

TC52140

Q9SUP5

Polygalacturonase

Cell Wall Modification

21

5.12

1613415_at

AB074999

TC45132

Q8W3L8

Xyloglucan endotransglycosylase 1

Cell Wall Modification

10

5.1

1615995_at

CF212592

-

P24806

Xyloglucan Endotransglucosylase 24

Cell Wall Modification

21

5.02

1615809_at

CB980277

TC69342

Q38908

Xyloglucan endotransglucosylase 30

Cell Wall Modification

11

4.87

1613719_at

CF214562

TC69710

Q7Y250

Arabinogalactan protein

Cell Wall Modification

2

4.8

1613528_at

CF513262

TC66769

Q8LPS9

Pectinesterase

Cell Wall Modification

2

4.56

1612668_at

CF519076

TC61610

Q5CHL3

Hydroxyproline-rich glycoprotein

Cell Wall Modification

21

4.32

1620063_at

CB921343

TC61082

Q9M3U4

β-1-3 glucanase

Cell Wall Modification

11

4.3

1611233_at

CF605724

TC66632

Q4W7I3

β-xylosidase

Cell Wall Modification

3

4.18

1622770_at

CF209970

TC66250

O65186

Cellulase

Cell Wall Modification

13

4.15

1609653_at

BQ797078

TC70494

Q9SBM1

Hydroxyproline-rich glycoprotein

Cell Wall Modification

10

4.15

1620618_at

BQ794587

TC55377

Q8LAB2

Proline-rich protein

Cell Wall Modification

2

3.59

1608799_at

BQ800204

TC58800

Q4ABV3

Pectinesterase

Cell Wall Modification

3

3.55

1616523_s_at

CF512513

TC63963

Q8L9T8

Arabinogalactan protein

Cell Wall Modification

1

3.53

1606652_at

CB969544

TC52628

Q8H1N7

Polygalacturonase

Cell Wall Modification

2

3.52

1622353_at

BQ800489

TC51768

Q5TIN5

β-6-xylosyltransferase

Cell Wall Modification

3

3.41

1619659_s_at

CF405842

TC68391

A1IIA8

Pectate lyase

Cell Wall Modification

14

3.37

1617920_at

CF609275

TC52380

Q6QLN2

Endo-1,4-β-glucanase

Cell Wall Modification

2

3.31

1608896_at

BQ796455

TC59657

Q5BM98

Secondary cell wall-related glycosyltransferase

Cell Wall Modification

4

3.24

1618849_at

BQ799201

TC63732

Q9SUP5

Polygalacturonase

Cell Wall Modification

21

3.16

1610996_at

BQ794786

TC63941

Q43111

Pectinesterase 3

Cell Wall Modification

14

3.15

1615125_at

CF372050

TC67073

Q5BM97

Secondary cell wall-related glycosyltransferase family 14

Cell Wall Modification

2

3.09

1608945_at

BQ793580

TC54729

P35694

Xyloglucan endotransglycosylase

Cell Wall Modification

15

3.09

1607567_at

BQ795116

TC54314

Q564G6

Galactomannan galactosyltransferase

Cell Wall Modification

11

3.06

1619068_at

CF215954

TC60314

Q94B11

Xyloglucan endotransglycosylase

Cell Wall Modification

3

2.78

1612425_at

CF371700

TC56348

Q6EP64

Hydroxyproline-rich glycoprotein

Cell Wall Modification

11

2.77

1616826_at

CB976610

TC54888

Q599J2

β-1,2 Xylosyltransferase

Cell Wall Modification

11

2.76

1609138_at

CF519079

TC66620

Q16861

Super cysteine rich protein

Cell Wall Modification

11

2.74

1617487_at

CD720403

TC54500

Q9SFF6

Pectinacetylesterase

Cell Wall Modification

2

2.69

1617687_at

CB981123

TC57577

Q494P2

Xyloglucan endotransglycosylase 2

Cell Wall Modification

21

2.67

1606832_at

CF214798

TC51861

Q7Y223

(1-4)-β-mannan endohydrolase

Cell Wall Modification

2

2.58

1617712_at

CF607664

TC67150

Q39789

Proline-rich cell wall protein

Cell Wall Modification

2

2.52

1617919_at

CF605842

TC55276

Q9SHZ2

β-1,3-glucanase

Cell Wall Modification

18

2.4

1617015_at

CF209172

TC54616

Q7XRM8

Pectate lyase

Cell Wall Modification

2

2.34

1618863_at

CF208339

TC52953

Q93Y12

α-glucosidase

Cell Wall Modification

3

2.28

1617939_s_at

CB910883

TC52435

Q41695

Pectinacetylesterase

Cell Wall Modification

1

2.28

1616734_at

CF405846

TC52115

Q6ZIF8

Pectin-glucuronyltransferase

Cell Wall Modification

3

2.28

1607945_at

AF243475

-

Q9M505

Pectate lyase

Cell Wall Modification

2

2.27

1612551_at

CF605967

TC63126

Q9M3C5

β-N-acetylhexosaminidase

Cell Wall Modification

21

2.26

1622843_s_at

CF212102

TC65557

Q9LVC0

Arabinogalactan protein

Cell Wall Modification

4

2.25

1611230_at

AF159124

-

Q9XGT3

β-galactosidase

Cell Wall Modification

2

2.25

1619468_at

AY043232

TC38735

Q94B16

Pectin methylesterase PME1

Cell Wall Modification

12

2.24

1610118_at

CB974025

TC60557

O23562

Glucanase

Cell Wall Modification

18

2.21

1614868_at

CB920940

TC64720

Q9M0S4

Arabinogalactan protein

Cell Wall Modification

5

2.17

1607528_at

AY043236

TC61627

Q94B12

Cellulase CEL1

Cell Wall Modification

21

2.11

1614814_s_at

CB345895

TC57381

O24136

CP12 precursor

Cell Wall Modification

13

2.07

Expansins play important roles in cell wall loosening via non-enzymatic mechanisms and are involved in cell expansion [36]. Most expansin genes displayed steadily increasing or decreasing patterns during berry development (see Table 1). Others showed peak expression around E-L stage 34 (α-expansin, 1608074_at, TC62965; α-expansin, 1608191_at, TC64448; Figure 4B). An expansin gene from strawberry, FaExp4, displays exactly the same peak transient expression pattern as these latter two genes at a comparable ripening stage as grape berries, called the White stage in strawberry fruits, just before red fruit color development [37]. Thus, these expansins in grape berry may be required during the Phase III of grape berry development, when the second phase of cell expansion occurs.

Terpenes, which are precursors for important aroma compounds [38], accumulate at véraison [39, 40]. One Unigene encoding a limonene cyclase (1613161_at; TC69794; Figure 4B), which is in the monoterpene pathway, is involved in the conversion of geranyl diphosphate into limonene [41]. Limonene and some of its derived compounds such as menthol or 1,8 cineol are intimately associated with the "eucalyptus fragrance" of red wine [42]. Accumulation of 1,8-cineole in wines is derived from precursors in grape, like limonene. The strong induction of our Unigene related to limonene cyclase (~40 fold from E-L stages 32 to 34) correlates well with the beginning of accumulation of 1,8-cineole in red grape samples [43]. One Unigene (1618595_at, TC53841; Figure 4B) belonging to profile 15 and encoding alcohol dehydrogenase exhibited strong homology with an (-) isopiperitenol dehydrogenase, which is involved in the same monoterpene pathway [44]. This transcript abundance of this Unigene is correlated to the expression of the limonene cyclase previously discussed above indicating a possible activation of these enzymes in the same metabolic pathway [44].

Phytohormone biosynthesis and responses

A number of plant growth regulators including abscisic acid (ABA), auxin (indole-3-acetic acid [IAA], brassinosteroids (BR), ethylene, and gibberellic acid (GA) have been implicated in the control of berry development and ripening. Therefore, steady-state transcript accumulation patterns of Unigenes with functions related to hormone biosynthesis and response were tracked over the course of berry development (Figure 5, Table 2).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-429/MediaObjects/12864_2007_Article_1142_Fig5_HTML.jpg
Figure 5

Expression of phytohormone transcripts. A) Black solid round (1608022_at, TC57089)-NCED isoform 1, red solid triangle (1607029_at, TC55541)-NCED isoform 4, green solid triangle (1614892_at, TC54474)-ABI1 protein phosphatase type 2C, blue solid diamond (1619802_at, TC67323)-RD22, orange solid square (1621346_at, TC65114)-ABI3 transcription factor. B) Black solid round (1617012_at, TC68057)-ethylene responsive factor 1, red solid triangle (1619585_at, TC62897)-ethylene induced transcription factor, green solid triangle (1621552_at, TC66829)-ethylene co-activator, blue solid diamond (1615952_s_at, TC56709)-aminocyclopropane carboxylic acid synthase, orange solid square (1622402_at, TC62349)-ERS1 ethylene receptor, lavender open square (1618518_at, TC55908)-EIN4/ETR5 ethylene receptor. *: transcript that does not pass the two-fold ratio. C) Black solid round (1617572_at, TC66046)-BRH1 brassinosteroid-responsive protein, red solid triangle (1612516_at, TC56501)-BRI1 brassinosteroid-responsive protein, green solid triangle (1619068_at, TC60314)-brassinosteroid-responsive protein, blue solid diamond (1608945_at, TC54729)-BRU1 brassinosteroid-responsive protein. *: transcript that does not pass the two-fold ratio. Black solid round (1618181_at, TC67464)-GIDL1 receptor, red solid triangle (1620071_at, TC56624)-GIDL2 Receptor, green solid triangle (1606777_s_at, TC56894)-GA1a gibberellin oxidase, blue solid diamond (1610610_at, TC66284)-gibberellic acid β hydroxylase. *: transcript that does not pass the two-fold ratio. E) Black solid round (1614660_at, TC53887)-auxin responsive protein (Aux22), red solid triangle (1613813_a_at, TC65541)-auxin responsive factor 2, green solid triangle (1609591_at, TC63193)-small auxin up RNA protein, blue solid diamond (1606566_at, TC62299)-SAUR protein, orange solid square (1616225_at, TC52772)-auxin responsive factor 18, lavender open square (1619610_at, TC56575)-IAA-amino acid hydrolase, brown open triangle (1611479_at, CD799903)-auxin transporter, pink open triangle (1617179_at, CF414958)-auxin efflux carrier, purple open diamond (1610034_at, TC59892)-auxin binding protein. F) Black solid round (1607601_at, TC61395)-12-oxophytodienoate reductase, red solid triangle (1614324_at, CF213899)-constitutive pathogen response 5 (CPR5), green solid triangle (1620306_at, TC69712)-cytokinin oxidase, blue solid diamond (1612955_at, TC52530)-Type-A response regulator.

Table 2

Transcripts (TFR pool) related to phytohormone biosynthesis and response categorized by the first hit in the MIPS2 catalog

Probeset ID

GenBank Annotation

VvGI5

UniProt ID

Gene Name Description

Function

Profile

Fold Change

1608022_at

BQ798105

TC57089

Q5SGD1

9-cis-epoxycarotenoid dioxygenase 1

ABA biosynthesis

15

6.46

1607029_at

CD716868

TC55541

Q8LP14

9-cis-epoxycarotenoid dioxygenase 4

ABA biosynthesis

15

3.85

1617541_s_at

CB342503

TC54423

O49814

β-carotene hydroxylase 2

ABA biosynthesis

3

3.25

1618171_s_at

BQ792407

TC55939

Q5SGC9

Zeaxanthin epoxidase

ABA metabolism

3

2.36

1614788_at

BQ792954

TC54112

Q3ZNL4

Dehydrin 1a

ABA response

11

26.63

1609063_at

BQ799245

TC63341

Q4VT47

RD-22 (ABA regulated)

ABA response

3

11.28

1621346_at

CB978597

TC65114

O48620

ABI3 (ABA regulated)

ABA response

14

7.57

1614892_at

CF511230

TC54474

O82468

Phosphatase 2C (ABA regulated)

ABA response

11

5.87

1615970_at

CF405892

TC65344

Q7XAV5

Dehydration responsive element binding protein

ABA response

15

4.53

1616735_at

CF604749

TC51916

O82176

Phosphate-induced protein (ABA regulated)

ABA response

16

3.44

1607955_at

CB978189

TC63879

Q9ZST5

PII protein (ABA regulated)

ABA response

12

3.07

1621396_at

CF514715

TC51970

Q94IB2

Phi-2 (ABA regulated)

ABA response

16

2.9

1617417_s_at

CD798528

TC61938

Q9M3V0

Phosphatase 2C (ABA regulated)

ABA response

5

2.77

1617791_s_at

CB004910

TC70554

Q45W74

Dehydration-induced protein (ABA regulated)

ABA response

4

2.55

1609665_a_at

CB005515

TC58443

Q9M9W9

Phosphatase-2C (ABA regulated)

ABA response

20

2.25

1609419_at

CB982969

CB982969

Q9S7V4

Abscisic acid-induced protein

ABA response

15

2.23

1610937_at

BQ792881

TC65459

Q67WL5

Abscisic acid-induced protein

ABA response

18

2.2

1611714_at

BQ794807

TC53528

Q06009

Phosphatase 2A (ABA regulated)

ABA response

3

2.12

1616882_at

CD799018

TC53254

Q7Y0S8

Phi-1 (ABA regulated)

ABA response

3

2.1

1621041_at

BQ794656

TC56829

Q9FIE3

Vernalization-insensitive protein 3 (ABA regulated)

ABA response

21

2.08

1619261_s_at

CB982969

TC68788

Q5XWP1

Abscisic acid-induced protein

ABA response

21

2.05

1619272_at

CF373376

TC51939

Q94AL8

Cold acclimation protein (ABA regulated)

ABA response

3

2.02

1619610_at

CB008850

TC56575

Q84XG9

IAA-amino acid hydrolase

Auxin metabolism

11

5.86

1615645_at

CB969433

TC62316

Q8LCI6

IAA-amino acid hydrolase

Auxin metabolism

3

3.19

1606566_at

CF211641

TC62299

Q681Q1

Auxin-induced protein

Auxin response

2

12.05

1609591_at

CD799271

TC63193

O23089

Auxin-regulated protein

Auxin response

11

11.74

1614851_s_at

CB973279

TC62879

Q1RY17

Auxin responsive Factor

Auxin response

3

11

1620662_at

CB981820

TC59676

Q6QUQ3

Auxin and ethylene responsive GH3

Auxin response

11

10.17

1614098_at

CF608417

TC57853

Q9FEL8

AUX1 like protein (influx carrier)

Auxin response

2

8.8

1606509_at

CB971327

TC52521

Q7XEJ9

Auxin induced protein

Auxin response

3

8.29

1616225_at

CB972698

TC52772

Q9C5W9

Auxin response factor 2

Auxin response

1

7.3

1612060_at

CB346335

TC53973

Q76DT1

AUX1 like protein (influx carrier)

Auxin response

7

6.96

1616104_at

CB004955

TC55019

O65695

Auxin-regulated protein

Auxin response

15

6.11

1612001_s_at

CF604676

TC69850

Q9XEY0

Nt-gh3 (auxin and ethylene)

Auxin response

2

4.69

1617163_at

BQ800616

TC56821

Q9SHL8

Auxin efflux carrier

Auxin response

3

4.23

1617513_at

CF203551

TC52262

Q8LAL2

Auxin-responsive protein IAA26

Auxin response

2

3.94

1613054_at

BQ794856

TC53877

O65695

Auxin regulated factor

Auxin response

3

3.79

1621946_at

CB975415

TC70724

Q8H0E0

PIN1 like auxin transport

Auxin response

7

3.7

1616015_at

CF607669

TC67186

Q2LAJ4

Auxin response factor

Auxin response

7

3.69

1611491_at

CB900901

TC57901

Q769J4

AtPIN3 (auxin efflux carrier)

Auxin response

20

3.5

1612180_at

CF608682

TC66988

Q6L8T9

Auxin responsive factor 5

Auxin response

7

3.49

1614660_at

CF207466

TC53887

P13088

Auxin-induced protein AUX22

Auxin response

11

3.04

1617179_at

CF414958

-

Q6YZX7

Auxin efflux carrier

Auxin response

21

2.91

1615728_at

AY082522

TC60981

Q84V38

CsIAA3 (Auxin regulated)

Auxin response

7

2.66

1610034_at

CB97302

TC59892

Q49RB8

Auxin receptor

Auxin response

10

2.45

1617097_at

BQ797969

TC67796

Q8LER0

Auxin efflux carrier

Auxin response

3

2.41

1613857_at

CD715051

TC55162

O24408

Auxin responsive factor

Auxin response

2

2.32

1607503_s_at

CF515267

TC53837

Q52QX4

Auxin-repressed protein

Auxin response

12

2.3

1619658_at

CF371851

TC66647

Q6QUQ3

Auxin and ethylene responsive GH3

Auxin response

15

2.25

1610591_at

CB923320

TC57860

Q3LFT5

Auxin regulated protein

Auxin response

10

2.21

1620726_at

CB339504

TC56077

Q6YZJ0

Auxin-regulated protein

Auxin response

3

2.19

1617694_at

CB972462

TC62076

Q93XP5

Auxin responsive factor

Auxin response

2

2.18

1618394_at

CF371644

CF371644

Q949J8

Auxin growth promoter protein

Auxin response

2

2.1

1617572_at

CB918599

TC66046

Q9XF92

BRH1 RING finger protein (Brassinosteroid regulated)

Brassinosteroid response

21

3.53

1620306_at

CF404552

TC69712

Q5ZAY9

Cytokinin oxidase

Cytokinin response

3

57.36

1610071_at

BQ797708

TC58750

Q39802

Cytokinin induced message

Cytokinin response

11

13.16

1619945_at

CB345883

TC61250

Q84N27

Cytokinin repressed protein

Cytokinin response

19

3.05

1622308_at

CF210289

TC63310

Q8S933

1-aminocyclopropane-1-carboxylate synthase

Ethylene biosynthesis

2

11.84

1615952_s_at

CF215641

TC56709

Q84X67

1-aminocyclopropane-1-carboxylic acid oxidase

Ethylene biosynthesis

3

6.56

1609683_at

CF604955

TC65735

Q5U8L6

Ethylene responsive factor 2

Ethylene response

12

22.64

1617012_at

CD802399

TC68057

P16146

Ethylene-responsive element

Ethylene response

11

14.05

1621552_at

BM437510

TC66829

Q9LV58

Ethylene-responsive transcriptional co activator

Ethylene response

21

9.08

1619585_at

CD800299

TC62897

Q75UJ4

Ethylene responsive factor

Ethylene response

13

4.21

1611910_s_at

AY395745

TC63214

Q6TKQ3

Ethylene responsive factor 4

Ethylene response

3

4.13

1609990_at

CB009298

TC63214

Q6TKQ3

Ethylene responsive factor 2

Ethylene response

3

4.12

1608511_at

CB342877

TC62587

Q6RZW7

Ethylene responsive factor 5

Ethylene response

15

3.72

1609780_at

CA810742

TC55438

Q94E74

Ethylene responsive factor 6

Ethylene response

3

3.22

1612699_at

BQ798614

BQ798614

Q9XIA5

Ethylene-forming-enzyme-like dioxygenase

Ethylene response

12

2.75

1619178_at

CB349106

TC54200

Q94E74

Ethylene responsive 6

Ethylene response

19

2.62

1613799_at

CF517211

TC55673

Q6RZW8

Ethylene responsive factor 4

Ethylene response

21

2.5

1622402_at

CD799344

TC62349

Q84PH6

Ethylene receptor (EIN4)

Ethylene response

20

2.4

1609559_at

CF215263

TC58568

Q94AW5

Ethylene-responsive element

Ethylene response

21

2.34

1606623_at

BQ797592

TC70037

Q9LVS8

EREBP-4

Ethylene response

3

2.28

1612921_at

CF514773

TC57403

Q9LVS8

EREBP-4

Ethylene response

3

2.26

1618213_at

CF203873

CF203873

Q9SWV2

ER6 (Ethylene regulated)

Ethylene response

3

2.16

1611657_at

CF208861

TC67832

O64588

GH3 Root formation (gibberellin regulated)

GA response

3

8.07

1610607_at

CF371650

TC66111

Q49RB3

GASA

GA response

3

6.98

1621228_at

BQ798029

TC52322

Q6S5L6

GAI protein (Gibberellin regulated)

GA response

7

2.52

1610610_at

CA810332

TC66284

Q9ZQA5

Putative gibberellin β-hydroxylase

Gibberellin metabolism

10

3.52

1620071_at

BQ800214

TC56624

Q9LYC1

Gibberellin receptor

Gibberellin response

11

5.3

1618181_at

CF512673

TC67464

Q9MAA7

Gibberellin receptor 2

Gibberellin response

16

2.1

1622456_at

CF609276

TC66424

Q7PCB5

Phytosulfokine

Growth factor

3

9.3

1616312_at

CD720049

TC61028

Q7PCA0

Phytosulfokine peptide precursor

Growth factor

12

3.69

1607170_s_at

CB917184

TC66717

Q7PCA1

Phytosulfokine

Growth factor

21

2.07

1612021_at

CF213898

CF213898

Q7EYF8

Phytosulfokine receptor

Growth factor response

3

4.06

1607601_at

CF209956

TC61395

Q76DL0

12-oxophytodienoate reductase

JA metabolism

2

4.2

1619407_s_at

CA809049

TC67104

Q76DL0

12-oxophytodienoate reductase

JA metabolism

21

2.92

1620308_at

CF208037

TC57918

Q38944

Steroid 5-alpha-reductase

Lipid, fatty acid and isoprenoid metabolism

3

3.5

1613941_at

CA818531

TC61611

Q7X9G5

Lipoxygenase

Lipid, fatty acid and isoprenoid metabolism

1

2.99

1618940_at

CF212858

TC64939

Q8W250

1-deoxy-D-xylulose 5-phosphate reductoisomerase

Lipid, fatty acid and isoprenoid metabolism

3

2.03

1613678_at

CB971023

TC54495

Q9M2G7

Phosphatase

Phosphate metabolism

3

2.07

1612552_at

CA818350

CA818350

Q9C9W8

S-adenosyl-L-methionine:salicylic acid carboxyl methyltransferase

SA response

11

6.99

1618457_at

CF205125

CF205125

Q9M6E7

UDP-glucose:salicylic acid glucosyltransferase

SA response

12

2.19

1619377_at

CF372632

TC68498

Q5Z825

avrRpt2-induced AIG2 protein

SA response

12

2.06

Abscisic acid

ABA amounts in berries decrease after anthesis, but then increase significantly at véraison [45]. External applications of ABA to ripening fruit can accelerate berry development (see [13] and references therein). The transcript abundance of 9-cis-epoxycarotenoid dioxygenase (NCED), which encodes the rate limiting step in ABA biosynthesis, increased during the lag phase and peaked at stage 35 around the start of véraison (Figure 5A). Both NCED1 (1608022_at, TC57089) and NCED4 (1607029_at, TC55541) had similar expression patterns, but differed significantly in their relative trancript abundance. A transcript (1614892_at, TC54474) encoding ABI1 (protein phosphatase 2C) showed an expression pattern like that of the NCED genes, but was more highly correlated with NCED4 than NCED1. The RD22 gene (1619802_at, TC67323), a dehydration-responsive protein, displayed a very large increase in abundance at véraison that continued to increase during berry maturation, whereas another transcript (1621346_at, TC65114) encoding an ABI3/VP1 (ABscisic acid Insensitive 3/ViviParous 1) transcription factor showed highest transcript abundance during the lag phase.

Ethylene

Traditionally, wine grape has been considered a non-climacteric fruit, however, there are studies that indicate that ethylene plays an important role in berry development and ripening [13] and is required for increased berry diameter and ripening processes, such as anthocyanin biosynthetic gene expression and accumulation [46, 47]. In addition, ethylene appears to be involved in controlling the expression of an alcohol dehydrogenase gene from grape [48]. Furthermore, some inhibitors of ethylene biosynthesis can delay berry ripening [49]. Ethylene-related transcripts displayed some very unique and intriguing patterns of expression (Figure 5B) indicating that this signaling pathway is differentially expressed along berry development. One transcript (1617012_at, TC68057) encoding a putative Ethylene Response Factor 1 (ERF1), a putative ethylene output gene, displayed a steady increase in abundance with maximal expression at ripening (Figure 5B) indicating a potential post-véraison role for this signaling pathway. An ethylene-induced transcription factor (1619585_at, TC62897) exhibited transcript accumulation during the lag (E-L stages 32 to 34) and early véraison (E-L stage 35) stages of development. A putative ethylene co-activator (1621552_at, TC66829) protein displayed biphasic peak transcript abundance at E-L stages 32 and 35. The transcript abundance of ACC oxidase (1615952_s_at, TC56709), the enzyme responsible for the last step in ethylene biosynthesis, was highest at E-L stage 32, the start of the lag phase, and then declined throughout the remainder of berry development. Interestingly, the transcript abundance of an ethylene receptor ERS1 (1622402_at, TC62349) and EIN4/ETR5 (1618518_at, TC55908) were at their lowest during E-L stages 32 to 33 until véraison, but then increased at a later stage (E-L stage 38). Ethylene pathway activation in grape berry appears to occur within a three week period of berry development (weeks 6 to 8 after anthesis; E-L stages 30 to 33) when the highest ethylene (ACC) content and transcript abundance of ACC oxidase were detected in Cabernet Sauvignon [46]. This hypothesis is supported by the observation that application of exogenous ethylene 8 weeks after anthesis hastened the ripening of the grape berries and resulted in a decrease in average cell size. In contrast, if the same ethylene treatment was applied during earlier stages of berry development (at 4, 5, 6 or 7 weeks), maturation was delayed [47].

According to the Arabidopsis model of ethylene signaling, reduced expression of transcripts and activity of receptors increases the sensitivity to ethylene, whereas increased receptor expression and activity decreases sensitivity [50]. In tomato, the expression of most genes encoding ethylene receptors increases during fruit development. In parallel, high levels of ethylene are expressed to counterbalance the negative effect of increased receptor expression on the ethylene signaling pathway [51]. In grape berry, the slight decreases observed in ethylene receptor transcript expression occurring between E-L stages 31 and 32 and the peak of ethylene accumulation during this same period, indicate a higher sensitivity to ethylene during the early stages of berry development. This would be expected to lead to a greater activation of the ethylene signaling pathway prior to véraison.

As in grape berry, strawberry is able to produce significant levels of ethylene during fruit development, but not to the same extent as climacteric fruits. Recently, three ethylene receptors have been identified in strawberry [52]. Two of them (FaEtr1 and FaErs1) display the same pattern of expression during fruit development as those observed for ERS1 ethylene receptor during grape berry development. In addition, the highest rates of ethylene production in strawberry were detected in very young green fruits. Following this, the hormone decreases continuously until the White stage of fruits. Following this stage, ethylene showed a slight but steady increase for the remainder of development. When considered together, the similarities of expression of ethylene receptors during fruit development for both grapes and strawberries coupled with the concomitant ethylene production during the early steps of fruit development indicate a conserved mechanism for ethylene perception between these fruits prior to ripening.

Brassinosteroids

Brassinosteroids (BR) have recently been implicated in playing an important role in berry development [53]. Castasterone concentrations are low during the early stages of berry development and then increase at véraison [53]. Brassinosteroids have been shown to increase cell size [54] indicating that berry enlargement may be affected by castasterone levels. BRH1 RING finger protein (1617572_at, TC66046) transcript abundance, which is known to be down-regulated by exogenous application of BR, decreased during E-L stages 31 to 35, but increased in fully mature berries (Figure 5C). The transcript abundance of the Brassinosteroid Receptor 1 gene (BRI1, 1612516_at, TC56501) peaks at the start of the lag phase (E-L stage 32) and then declines thereafter. The transcript abundance of BRU1 (1608945_at, TC54729), which is a BR-responsive transcript encoding a xyloglucan endotransglycosylase (XET), showed a transient increase in abundance at véraison. In the same family, transcripts for another BR-responsive protein (1619068_at, TC60314) declined with berry development. Clearly, there are many significant changes in transcript abundance that are associated with brassinosteroid responses during berry development.

Gibberellins

Very little is known about the role of gibberellin (GA) in grape berry development except a possible role in cell enlargement. Biologically active concentrations of GA are high in flowers and in fruits just after anthesis, but then drop to lower levels over the course of berry development [53, 55]. There is a second peak of active GA at the start of the lag phase and it is 77 times higher in the seed compared to the berry mesocarp [56]. The transcript abundance of two putative GA receptors, GIDL1 and GIDL2 (1618181_at, TC67464; 1620071_at, TC56624, respectively), increased during berry development (Figure 5D). Interestingly, the transcript abundance of the GA signaling pathway repressor, GAI1 (1606777_s_at, TC56894), declines transiently at véraison. The transcript abundance of a putative GA β-hydroxylase (1610610_at, TC66284) declines over the course of berry development (Figure 5D) more or less coincident with the known accumulation pattern of GA1 in developing berries.

Auxins

The mechanisms by which the phytohormone indole-3-acetic acid (IAA) regulates berry development are complex and not fully understood. Increased auxin production produced through the action of an ovule-specific auxin-synthesizing transgene enhanced fecundity in grapes [57]. Earlier reports indicated that auxin concentrations were high during early Phase I and declined following véraison [55] consistent with the role of this phytohormone in promoting cell division and expansion during Phase I. Treatment of grape berries with synthetic auxin-like compound, benzothiazole-2-oxyacetic acid (BTOA) delayed ripening [45]. A more recent study showed that auxin concentrations remain relatively constant over the course of berry development [53].

Our data indicate that there are numerous transcript responses to auxin (Figure 5E). The transcript abundance of Aux22 (1614660_at, TC53887), which forms heterodimers with auxin response factors (ARF) in order to repress auxin responses, increased after véraison (Figure 5E). Transcripts for both Auxin Response Factor 2 (ARF2, 1613813_a_at, TC65541) and a Small Auxin Up RNA protein (SAUR) (1609591_at, TC63193) increased after véraison, whereas transcripts for a different SAUR transcript (1606566_at, TC62299) and an Auxin-induced Response Factor, ARF18 (1616225_at, TC52772) both declined in a very similar pattern during berry development. A transcript (1619610_at, TC56575) encoding IAA-amino acid hydrolase, which is involved in IAA homeostasis, was highly expressed during the later stages of berry development (Figure 5E). The synthesis and hydrolysis of IAA conjugates, which function in both permanent inactivation and temporary storage of auxin [58], may play an important role in the control of IAA concentrations as berry development progresses. IAA-amino acid hydrolase may provide for local concentrations of auxins within the berries to promote mesocarp cell enlargement. Several transcripts (1611479_at, CD799903; 1617179_at, CF414958; 1610034_at, TC59892) related to auxin transport and perception also displayed increased abundance at the onset of véraison. Given the importance of auxin-mediated processes in developing berries, more research needs to be conducted to elucidate the mode of action of auxin signaling and response pathways.

Methyl jasmonate and cytokinins

Methyl jasmonate (MeJA) is known to promote the synthesis and accumulation of terpenes and resveratrol in berry cell cultures [59, 60], however, its effects in vivo are not well understood. The transcript abundance of 12-oxophytodienoate reductase (12-OPR) (1607601_at, TC61395), which is involved in jasmonate biosynthesis [61], and a constitutive pathogen-response 5 protein (1614324_at, CF213899), both decreased with berry development (Figure 5F). Less is known about the role of cytokinins in berry development. The transcript abundance of cytokinin oxidase (1620306_at, TC69712), which degrades cytokinin [62], decreased over berry development, whereas a known cytokinin-response regulator, a Type-A response regulator (1612955_at, TC52530), showed a steady increase in transcript abundance over berry development (Figure 5F).

New candidates genes associated with calcium signaling, flavonoid transport and flavor

Calcium has many essential roles in plant growth and development [63], however, the role of calcium signaling in grape berry development is largely unexplored. Recently, an ABA-responsive calcium-dependent protein kinase (CDPK) was described that was specifically expressed in the seed and flesh of berries with increased transcript abundance over berry development and ripening [64]. In the current study, a large number of genes with functions related to calcium sequestration, transport and signaling were found to display developmentally regulated expression patterns (Figure 6A; Table 3).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-429/MediaObjects/12864_2007_Article_1142_Fig6_HTML.jpg
Figure 6

Expression of potential candidates Unigenes. A) Black solid round (1614028_at, TC67285)-cation-transporting ATPase, red solid triangle (1622073_at, CF404214)-calcium-transporting ATPase, green solid triangle (1617237_s_at, TC66680)-Ca2+/H+ exchanger, blue solid diamond (1618587_at, TC64370)-calmodulin-repressor of gene silencing. B) Black solid round (1619917_s_at, TC69505)-glutathione-S-transferase, red solid triangle (1609870_at, TC58286)-glutathione-S-transferase conjugating ATPase, green solid triangle (1607560_at, TC62162)-multi-drug secondary transporter like protein (MATE), blue solid diamond (1611091_s_at, TC54724)-VvMYBPA1, orange solid square (1618504_at, TC61713)-MYC transcription factor. C) Black solid round (1608603_at, TC56956)-phloroglucinol O-methyltransferase, red solid triangle (1613542_at, TC62584) O-methyltransferase, green solid triangle (1620469_at, CF209780)-O-methyltransferase, blue solid diamond (1616348_at, TC52353)-S-adenosyl-L-methionine:benzoic acid/salicylic acid carboxyl methyltransferase orange solid square (1612552_at, TC57170)-S-adenosyl-L-methionine:salicylic acid carboxyl methyltransferase.

Table 3

Transcripts (TFR pool) related to calcium categorized by the first hit in the MIPS2 catalog

Probeset ID

GenBank Annotation

VvGI5

UniProt ID

Gene Name Description

Function

Profile

Fold Change

1616662_at

CF404703

TC59643

Q9LIK7

Ca2+/ATPase

Ca transport

3

27.96

1617237_s_at

CF207946

TC66680

O64455

Ca2+/H+ exchanger (VCAX1)

Ca transport

14

2.56

1614028_at

CB976052

TC62785

Q7X8B5

Ca2+-transporting ATPase 8

Ca transport

16

2.32

1619731_at

CB972437

CB972437

Q93YX7

Type IIB calcium ATPase

Ca transport

21

2.2

1622073_at

CF404214

CF404214

Q9LIK7

Calcium-transporting ATPase 13

Ca transport

5

2.05

1615486_at

CF415476

TC69351

Q5D6H2

Cyclic Nucleotide-Gate Channel 2

Ion channel

3

8.21

1621591_at

CB981532

TC66482

Q94AS9

Cyclic nucleotide-gated ion channel 4

Ion channel

10

3.01

1609527_at

CD802146

TC64117

Q6ZHE3

Cyclic nucleotide-binding transporter 1

Ion channel

8

2.06

1613268_at

CB342482

TC53213

O65717

Cyclic nucleotide-gated ion channel 1

Ion channel

12

2.05

1614456_at

BQ797488

BQ797488

Q8L706

Ca2+-dependent lipid-binding protein

Lipid binding

11

3.83

1614582_at

BQ799084

BQ799084

Q8LJ85

Calreticulin

Protein folding and stabilization

12

2.37

1611917_at

CB972164

TC58290

Q39817

Calnexin

Protein folding and stabilization

1

2.31

1612291_at

CB347450

TC67746

P93508

Calcium-binding protein

Protein folding and stabilization

3

2.2

1622324_at

CF568845

TC63952

Q39817

Calnexin

Protein folding and stabilization

1

2.04

1612443_at

CF211151

TC68392

Q7X996

CBL-interacting protein kinase 20

Signal transduction

11

12.97

1610295_at

BQ797947

TC57947

Q8W1D5

CBL-interacting protein kinase 5

Signal transduction

4

12.35

1618587_at

CF518131

TC64370

Q9AXG2

Calmodulin

Signal transduction

21

11.43

1618447_at

CA815141

TC53225

Q6ETM9

CBL-interacting protein kinase 21

Signal transduction

3

7.75

1611127_at

CF510878

TC64442

Q8L3R2

Calmodulin

Signal transduction

12

5.33

1610922_at

CF404315

TC68116

Q1SFZ7

CBL-interacting protein kinase 21

Signal transduction

3

3.43

1606980_at

CF211606

TC69501

Q008R9

Calcium sensor homolog

Signal transduction

2

3.23

1618045_at

CF216119

TC53057

Q676U1

CBL-interacting protein kinase 20

Signal transduction

21

2.9

1611172_at

CB003645

TC52484

Q8LK24

SOS2-like protein kinase

Signal transduction

16

2.81

1612269_at

CB345885

TC53895

Q3HRN8

Calcineurin B

Signal transduction

13

2.74

1606859_at

CF518881

CF518881

Q3HRN8

Calcineurin B

Signal transduction

13

2.74

1613576_s_at

CF201676

TC60874

P62200

Calmodulin 1/11/16

Signal transduction

11

2.7

1622351_at

CA810859

TC60874

P62200

Calmodulin 1/11/16

Signal transduction

11

2.26

1611555_at

CB971903

TC54154

Q9SS31

Calmodulin-related protein 2

Signal transduction

13

2.22

1608587_at

CD799705

TC62151

Q5D875

Calcium-dependent protein kinase CDPK1444

Signal transduction

10

2

1614600_s_at

CF213754

TC52150

Q9ZT86

Calcium-binding protein

Unclassified protein

7

2.89

1616580_at

CF206767

TC55591

Q84Y18

CAX-interacting protein 4

Unclassified protein

11

2.63

Calcium homeostasis within the cytosol is tightly controlled by membrane spanning Ca2+-ATPases and H+/Ca2+ exchangers, which typically maintain low concentrations of Ca2+ in the cytosol and restore this concentration following signaling-related transient changes in calcium levels. Transcripts encoding plasma membrane Ca2+-ATPase genes (1614028_at, TC62785; 1622073_at, CF404214), which are closely related to ACA8 and ACA13, respectively, in Arabidopsis thaliana, showed increased transcript abundance during E-L stages 33 and 34 and in later developmental stages. Interestingly, ABA markedly and rapidly stimulates the expression of the ACA8 gene in cell cultures of Arabidopsis thaliana [65]. A tonoplast Ca2+/H+ exchanger (1617237_s_at, TC66680), which is a close homolog of CAX3 from A. thaliana and plays a key role in cytosolic Ca2+ homeostasis [66], showed a transient increase in transcript abundance at E-L stages 34, indicating a possible role for calcium signaling around véraison.

ABA accumulates until two weeks after the beginning of véraison before decreasing later in berry development [67]. Thus, it is likely that ABA is directly or indirectly involved in the control of Ca2+ signaling and homeostasis events, particularly around véraison.

The increased expression of several Unigenes encoding calmodulin or calcium interacting protein kinases (see Table 3) supports this hypothesis [68]. One Unigene encoding a calmodulin-related suppressor of gene silencing (1618587_at, TC64370) displayed a pronounced pattern with two peaks of expression at E-L stage 32 and at E-L stage 35 corresponding to two transitions of berry development (Phases I to II and Phases II to III). This Unigene displayed a 10-fold change in its transcript abundance across berry development and may be involved in the suppression of posttranscriptional gene silencing (PTGS) by interacting with a proteinase known to suppress PTGS in plants [69]. This correlation indicates a possible role for calcium in regulating the activity of the PTGS mechanisms. To date, only one paper reported the possibility of the involvement of PTGS in the regulation of gene expression during plant development [70]. Further investigations are necessary to evaluate the real impact of this Unigene in the triggering of véraison.

Phenolic compounds, derived from flavonoids (anthocyanins, tannins and flavonols), are the major wine constituents responsible for organoleptic properties such as color and astringency. Twenty-one Unigenes encoding biosynthetic enzymes of the general phenylpropanoid and flavonoid pathways were found to exhibit differential mRNA expression patterns across berry development (Table 4). The vast majority of these genes are expressed predominantly in the skin [71].
Table 4

Transcripts (TFR pool) related to flavonoid metabolism categorized by the first hit in the MIPS2 catalog within specific sub-sections of the flavonoid pathway

Probeset ID

GenBank Annotation

VvGI5

UniProt ID

Gene Name Description

Function

Profile

Fold Change

1617171_s_at

AF000371

TC51696

O22303

UDP glucose:flavonoid 3-o-glucosyltransferase (UFGT)

Anthocyanin Pathway

11

46.79

1614441_at

BQ798241

TC57653

Q9SWY6

Anthocyanidin synthase (ANS)

Anthocyanin Pathway

11

12

1618112_at

CB971725

TC70789

Q9LTA3

Anthocyanidin-3-glucoside rhamnosyltransferase

Anthocyanin Pathway

3

9.39

1611309_at

CF210457

TC58629

Q8H1R1

Dihydroflavonol 4-reductase (DFR)

Common Pathway

19

7.36

1611739_at

CF403783

TC64266

Q8H224

Flavonoid 3'-hydroxylase (F3'H)

Common Pathway

2

5.68

1620675_at

CB969894

TC51699

P93799

Dihydroflavonol 4-reductase (DFR)

Common Pathway

3

5.21

1617019_at

BQ800456

TC67173

O80407

Chalcone synthase (CS)

Common Pathway

3

5.17

1607739_at

CF415693

TC70298

P41090

Flavanone 3-hydroxylase (F3H)

Common Pathway

3

2.93

1608379_at

CF202029

TC40489

Q8H8H7

Flavanone 3-hydroxylase (F3H)

Common Pathway

21

2.55

1607732_at

AF020709

TC63806

O22519

Chalcone synthase (CS)

Common Pathway

3

2.48

1608761_at

CB982029

TC53331

Q9FLV0

Flavanone 3-hydroxylase (F3H)

Common Pathway

18

2.02

1611542_at

CB971080

TC51691

P43311

Polyphenol oxidase (PPO)

Flavonoid Catabolism

3

28.9

1622651_at

CF215945

TC58764

P93622

Polyphenol oxidase (PPO)

Flavonoid Catabolism

5

3.79

1608791_at

CB978059

TC66577

Q84TM1

Flavonol synthase (FLS5)

Flavonol Pathway

3

5.12

1621051_at

CN006197

-

Q40285

Flavonol 3-O-glucosyltransferase

Flavonol Pathway

13

3.94

1615401_at

CB342555

TC55331

Q40285

Flavonol 3-O-glucosyltransferase

Flavonol Pathway

15

2.43

1618155_at

CD004374

TC54048

Q40288

Flavonol 3-O-glucosyltransferase 6

Flavonol Pathway

10

2.27

1612134_at

CF204393

TC53206

Q5FB34

Anthocyanin reductase (ANR)

Proanthocyanidin Pathway

3

34.12

1615174_s_at

CD011073

TC68741

Q4W2K6

Leucoanthocyanidin reductase 2 (LAR2)

Proanthocyanidin Pathway

13

4.08

1608212_at

CK138122

TC54322

Q84V83

Leucoanthocyanidin reductase 2 (LAR2)

Proanthocyanidin Pathway

13

3.52

The mechanisms by which anthocyanins accumulate in the vacuole of grape berry skin cells during Phase III are not fully understood. These compounds must be transported from the site of synthesis in the cytosol to their final destination, the vacuole. Several models have been proposed for sequestering anthocyanins in the vacuole in Arabidopsis thaliana. One model [72] indicates the action of a glutathione-S-transferase (GST) in facilitating the transfer of anthocyanins into the vacuole. Another model indicates that a transporter of the multidrug-resistance-associated protein family could facilitate the transport of an anthocyanin-GST complex into the vacuole [73]. Here, the Unigene transcript encoding a GST (1619917_s_at, TC69505; Figure 6B) displayed a 63-fold increase in abundance during the stages in berry development in which flavonoids accumulate (Figure 6B). This Unigene is closely related to a GST homolog known to be involved in anthocyanin sequestration [74]. This Unigene also displays a skin-specific expression pattern [71], which is consistent with the tissue localization of anthocyanins. A Unigene homologous to a glutathione-S-conjugate transporting ATPase (1609870_at, TC58286) showed a peak of expression at véraison (E-L stage 34). While not yet characterized in detail, this Unigene belongs to the ABC transporter sub-family, members of which are known to transport anthocyanins [74]. The putative multi-drug transporter (1607560_at, TC62162), which is known to be involved in the sequestration of tannins into vacuoles [75], exhibited peak transcript abundance at E-L stage 32 followed by a decline, and is consistent with the pattern of maximal tannin accumulation that occurs a few weeks before véraison.

Specific members of the MYB transcription factor family play critical roles in the regulation of flavonoid metabolism during grape berry development [76]. We detected four transcripts encoding MYB transcription factors that have been previously characterized in grape berry (see Table 4) [7780]. VvMYBPA1 (1611091_s_at, TC54724) regulates the proanthocyanidin (condensed tannins) pathway in the grape berry [77]. In the Shiraz cultivar, VvMYBPA1 peak expression appears to occur during E-L stages 34 and 35 in the skin and seeds, whereas, in Cabernet Sauvignon this gene is expressed at an earlier developmental stage (E-L stages 32) (Figure 6B). Such differences are likely to be cultivar-dependent. In the same way, the MYC family of transcription factors also plays a key role in regulation of the anthocyanin pathway. One MYC transcription factor transcript (1618504_at, TC61713), which shares strong amino acid sequence identity with MYC genes known to be involved in the regulation of anthocyanin production [81], displayed a pattern of transcript accumulation that decreased from the beginning of berry development until E-L stage 35 and then increased for the remainder of fruit development (Figure 6B). Furthermore, this Unigene is preferentially expressed in the skin [71]. These expression patterns correlate well with the accumulation of anthocyanins and proanthocyanins.

In grape berries, volatile aroma compounds, such as terpenes, benzenoids, and phenylpropanoids, accumulate in exocarp and mesocarp tissues following the initiation of berry ripening [38, 82]. Three transcripts (Figure 6C) encoding O-methyltransferases, which may participate in the biosynthesis of volatile compounds, were also detected [83]. The first Unigene (1608603_at, TC56956), which encodes a putative phloroglucinol O-methyltransferase, is involved in the biosynthesis of volatile 1,3,5-trimethoxybenzene, a compound not previously described in grape [83], displayed a very high transcript abundance at the beginning of berry development (E-L stage 31) before decreasing after véraison until E-L stage 36 and then increasing again in mature berries (Figure 6C). The second Unigene (1613542_at, TC62584) was expressed at E-L stage 31, but then declined. The third Unigene (1620469_at, CF209780) displayed very low transcript abundance with a slight increase following véraison (Figure 6C). Finally, two S-adenosyl-L-methionine (SAM):salicylic acid carboxyl methyltransferases were identified with developmentally-induced expression patterns. The first Unigene (1616348_at, TC52353) showed a broad peak of expression between E-L stages 32 to 35, whereas the second Unigene (1612552_at, TC57170) showed increased transcript abundance after véraison (E-L stage 34) (Figure 6C). Such genes are thought to play important roles in scent production or plant defense [84]. Little correlation between the level of sequence similarity and the structural similarity of their substrates has been observed for most of these protein families, so that gene functions have to be assigned following detailed biochemical testing [85].

Organic acid and proline metabolism

The acid:sugar balance at harvest is an important factor of wine quality as it affects important sensory attributes [15]. Two major organic acids that contribute to titratable acidity, tartrate and malate, are the most abundant organic acids in grapes and reach maximal concentrations around the end of Phase I (E-L stage 32; see Table 5). Tartrate concentrations were found to peak at E-L stage 32 and then declined steadily until harvest, E-L stage 38 (Figure 7A). Tartrate concentrations decreased in parallel with three different transcripts encoding L-idonate dehydrogenase (1622252_at, TC52651; 1613165_s_at, TC52651; 1612918_at, TC52651), a key enzyme in tartrate biosynthesis [86]. The innermost region of the berry pulp surrounding the seed has been shown to contain the highest tartrate concentrations [87]. Consistent with this observation, tartrate synthase transcripts have been shown to be more abundant in seeds than in outer mesocarp and skin tissues [71].
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-429/MediaObjects/12864_2007_Article_1142_Fig7_HTML.jpg
Figure 7

Organic acids and amino acids: metabolites and transcripts. A) Black solid round-tartrate, red solid triangle (1622252_at, TC52651)-L-idonate dehydrogenase, green solid triangle (1613165_s_at, TC52651)-L-idonate dehydrogenase, blue solid diamond (1612918_at, TC52651)-L-idonate dehydrogenase. B) Black solid round-malate, red solid triangle (1612546_at, TC68207)-cytosolic MDH, green solid triangle (1609147_at, TC55437)-cytosolic MDH, blue solid diamond (1622059_at, TC69439)-mitochondrial malate dehydrogenase (MDH), orange solid square (1617448_at, TC54982)-mitochondrial MDH, lavender open square (1609345_s_at, TC57092)-malic enzyme. C) Black solid round-proline, red solid triangle (1619565_at, TC52705)-pyrroline-5-carboxylate synthetase, green solid triangle (1617293_s_at, BQ792635)-proline dehydrogenase, blue solid diamond (1610800_at, CK906448)-proline transporter. *: Transcripts that do not pass the two-fold ratio. All compounds amounts were normalized by a ribitol standard (25 mg/L).

Table 5

Transcripts (TFR pool) related to organic and phenolic acid metabolism

Probeset ID

GenBank Annotation

VvGI5

UniProt ID

Gene Name Description

Function

Profile

Fold Change

1608526_at

CB974198

TC66314

Q5NBP4

AOBP-like protein

Organic Acid

11

6.48

1618209_at

CF373021

TC56127

P82281

Ascorbate peroxidase

Organic acid

3

3.59

1617448_at

BQ795936

TC54982

Q9M6B3

Malate dehydrogenase

Organic Acid

10

3.48

1606935_at

CB969531

TC66898

Q9SAK4

Succinic semialdehyde dehydrogenase 1

Organic acid

3

3.05

1620641_at

CF511421

TC52472

Q39540

AOBP-like protein

Organic Acid

9

2.11

1611871_at

CF415063

TC54132

Q84UH4

Dehydroascorbate reductase

Organic Acid

19

2.1

1609147_at

CB979150

TC55437

Q645N0

Malate dehydrogenase (cytosolic)

Organic Acid

11

2.01

1607417_at

CF512464

TC53733

Q8L7U8

Cinnamyl-alcohol dehydrogenase CAD1

Phenolic Acid

2

80.03

1614643_at

CF214966

TC51729

Q43237

Caffeoyl-CoA O-Methyltransferase

Phenolic Acid

2

34.34

1611265_at

CF513719

TC51900

Q49LX7

4-coumarate:CoA ligase

Phenolic Acid

11

25.11

1620342_at

CF207053

TC64352

Q00763

Caffeic acid 3-O-methyltransferase 1

Phenolic Acid

11

18.69

1610935_at

CF404728

TC64481

Q75W19

Ferulate-5-hydroxylase (FAH1)

Phenolic Acid

2

13.64

1619682_x_at

CF205002

TC62835

Q9M560

Caffeic acid O-Methyltransferase

Phenolic Acid

2

13.58

1616434_s_at

AF239740

TC62835

Q9M560

O-methyltransferase

Phenolic Acid

2

11.53

1609307_at

CD715818

TC66040

O24145

4-coumarate--CoA ligase (At4CL1)

Phenolic Acid

2

10.6

1619450_s_at

CF215109

TC52364

Q00763

O-methyltransferase

Phenolic Acid

2

10.28

1607475_s_at

CD012393

TC64352

Q3SCM5

Caffeic acid O-methyltransferase

Phenolic Acid

11

9.32

1614423_at

CF517687

TC66815

Q6DMZ8

Cinnamoyl CoA Reductase

Phenolic Acid

2

8.61

1620650_s_at

CF207485

TC69704

Q9ATW1

Cinnamyl-alcohol dehydrogenase

Phenolic Acid

1

5.95

1616191_s_at

CB971061

TC70715

Q3HM04

Cinnamate-4-Hydroxylase

Phenolic Acid

3

5.78

1613542_at

CF209028

TC62584

Q7X9J0

O-methyltransferase

Phenolic Acid

2

5.54

1622267_at

CF516149

TC64537

O65152

Cinnamyl-alcohol dehydrogenase

Phenolic Acid

3

4.48

1619320_at

CB974305

TC66743

P31687

4-coumarate:CoA ligase 3 (4CL3)

Phenolic Acid

3

4.21

1619808_at

CB972340

TC54722

O65152

Cinnamyl-alcohol dehydrogenase

Phenolic Acid

3

3.96

1611249_s_at

CF517155

TC51769

O65152

Cinnamyl-alcohol dehydrogenase

Phenolic Acid

3

3.93

1613831_at

CD801016

TC58955

Q5I6D6

Sinapyl alcohol dehydrogenase

Phenolic Acid

3

3.36

1613548_at

CB009193

TC68990

Q8H8C9

4-coumarate:CoA ligase

Phenolic Acid

11

3.19

1615439_at

CF213244

TC63112

P30359

Cinnamyl alcohol dehydrogenase 2

Phenolic Acid

2

2.38

1609327_at

CF208599

TC68572

A1YIQ2

Cinnamyl-alcohol dehydrogenase 1

Phenolic Acid

2

2.33

1607163_at

CF415171

-

Q8LSQ3

4-coumarate:CoA ligase

Phenolic Acid

3

2.22

1613511_at

BQ796246

TC59682

Q65CJ7

Hydroxyphenylpyruvate reductase

Phenolic Acid

11

2.22

1616445_at

CD716014

TC57545

Q9LYJ0

Cinnamoyl CoA Reductase

Phenolic Acid

16

2.11

Like tartrate, malate concentrations peaked around E-L stage 32, but then declined more rapidly than tartrate during berry ripening (Figure 7B). In contrast to the good correlation between tartrate and L-idonate dehydrogenase transcript abundance, there is a less obvious correlation between malate concentrations and the transcript abundance of Unigenes encoding malate dehydrogenases (Figure 7B). Transcript abundance for two isogenes encoding cytosolic NAD-dependent malate dehydrogenases (1612546_at, TC68207; 1609147_at, TC55437), which catalyze the interconversion of malate to oxaloacetate, increased during ripening. Transcripts for mitochondrial isoforms of the enzyme (1622059_at, TC60439; 1617448_at, TC54982) also increased over this same time period. In contrast, the transcript abundance of a NADP-dependent malic enzyme (1609345_s_at, TC57092), which catalyzes the oxidative decarboxylation of malate to pyruvate, declined slightly from E-L stages 34 to 36, but then increased by stage 38 (Figure 7B). The slight increase in the expression of all of these enzymes together may contribute to the declining concentrations of malate during ripening. Very little is known about the mechanisms of malate transport processes in the phloem/xylem and within developing grape berries. The regulation of malate concentrations in berries appears to be quite complex. More research is needed to elucidate this well known developmental process.

Mature berries contain unusually high concentrations of free proline; proline being the most abundant amino acid in Cabernet Sauvignon [88, 89]. Proline concentrations increased significantly at véraison and remained high until berries were fully ripe (Figure 7C). Transcripts encoding pyrroline-5-carboxylate synthetase (1619565_at, TC52705), the key regulatory enzyme in proline biosynthesis, remained relatively constant with a small peak of expression occurring at E-L stage 35 (Figure 7C). Proline dehydrogenase transcripts (1617293_s_at, BQ792635), which encode the first enzymatic step in proline catabolism, increased only during the latter stages of berry development. These mRNA expression patterns are consistent with earlier reports and with protein expression patterns of these enzymes [88]. Proline accumulation correlated poorly with steady-state transcript and protein abundance changes for these two enzymes indicating that proline production is regulated by posttranslational mechanisms [88]. Steady-state transcripts encoding a proline transport protein (1610800_at, CK906448) also increased in conjunction with proline abundance.

Sugar metabolism

Sugar accumulation in grape berries has been well studied because sugar content is a key factor in producing wine. In contrast to organic acids, hexose sugars (i.e., Glc and Fru) begin to accumulate substantially in the lag phase (Phase II) and continue thereafter. In grapevines, carbohydrates produced during photosynthesis are exported from the leaf as sucrose and transported in the phloem to the berry cluster [90, 91]. Prior to véraison, most sugars imported into the berries are metabolized with little if any storage of these compounds. Following véraison, however, sugars accumulate in the vacuole to high levels in the form of glucose and fructose following the enzymatic cleavage of sucrose (mainly in the apoplast, but also in the cytoplasm and vacuole). Monosaccharide transporters direct the transport of these sugars through different organelles [92].

In the berries in this study, fructose was more abundant than glucose; in contrast sucrose concentrations remained relatively low and constant throughout berry development (Figure 8A). Transcript abundance for the Unigene encoding sucrose synthase (1609402_at, TC62599), increased gradually over berry development consistent with increased hexose accumulation in the berry. This Unigene has high homology with the sucrose synthase (CiTSUSA) in Citrus unshiu [93]. CiTSUSA also increases with fruit development and catalyzes the reaction in the cleavage direction (sucrose to UDP-glucose and fructose). Komatsu et al. [93] suggest that the action of this gene may be important for sink strength.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-429/MediaObjects/12864_2007_Article_1142_Fig8_HTML.jpg
Figure 8

Hexose sugars, transporters, and starch: metabolites and transcripts. A) Black solid round-fructose, red solid triangle-glucose, green solid triangle-sucrose. B) Black solid round (1609402_at, TC62599)-sucrose synthase, red solid triangle (1608257_at, TC68135)-sucrose-6-phosphate phosphatase, green solid triangle (1611613_at, TC60693)-invertase (GIN1), blue solid diamond (1612836_at, TC57719)-invertase (GIN2), orange solid square (1620628_at, TC67908)-neutral invertase, lavender open square (1611027_at, TC56057)-acidic invertase, brown open triangle (1616255_at, TC57339)-fructokinase. C) Black solid round (1616083_at, TC51694)-VvHT1 (hexose transporter 1), red solid triangle (1615257_at, TC65400)-VvHT6 (hexose transporter 6), green solid triangle (1615697_at, TC51724)-VvSUC27 (sucrose transporter), blue solid diamond (1608991_at, TC60060)-plastidial glucose transporter, orange solid square (1613408_at, TC66667)-polyol transporter, lavender open square (1619379_at, TC58801)-plastidial triose phosphate transporter, brown open triangle (1622157_at, TC61733)-plastidial triose phosphate transporter. D) Black solid round (1615571_at, TC53551)-starch synthase, red solid triangle (1613601_at, TC67353)-starch synthase, green solid triangle (1617068_at, TC54621)-plastidial alpha-glucan, water dikinase, blue solid diamond (1617941_at, TC62494)-plastidial alpha-glucan, water dikinase, orange solid square (1622120_at, TC54533)-starch phosphorylase, lavender open square (1613188_at, TC70258)-α-amylase, brown open triangle (1617124_at, TC67979)-β-amylase. All compounds amounts were normalized by a ribitol standard (25 mg/L).

Sucrose-6-phosphate phosphohydrolase (SPP) (1608257_at, TC68135), which catalyzes the last step in sucrose synthesis, showed a slight increase in transcript abundance after E-L stage 32 and then remained relatively constant throughout the remainder of berry development (Figure 8B). In contrast, the transcript abundance of two vacuolar invertases, GIN1 and GIN2 (1611613_at, TC60693; 1612836_at, TC57719), which catalyze the catabolism of sucrose to fructose and glucose, declined over the course of berry development (Figure 8B), consistent with an earlier report [94]. The mRNA expression of these two invertases is consistent with the early increases in sugar accumulation during Phase II (E-L stages 32 to 34). On the other hand, transcript abundance for a neutral invertase (1620628_at, TC67908) and a cell wall acid invertase (1611027_at, TC56057) remained relatively constant during the course of berry development consistent with earlier reports on the amount and activity of these enzymes in developing berries [95]. In grape berries, sucrose cleavage is largely catalyzed by cell wall bound invertases [95]. Sucrose cleavage is usually associated with cell wall invertase activity at the onset of ripening, together with a shift towards apoplastic phloem unloading of sugars in berries during this same period of time [95]. Finally, transcripts encoding fructokinase (1616255_at, TC57339), which catalyzes the formation of fructose-6-phosphate and may regulate starch formation, declined in abundance in a similar manner as GIN1 and GIN2 following a peak of expression at E-L stage 32.

In most sink cells, sucrose is either cleaved by invertase into glucose and fructose or degraded by sucrose synthase into uridine-5'-diphosphate (UDP) glucose and fructose for subsequent metabolism and biosynthesis [96, 97]. Cell wall invertases appear to play the main role in the cleavage of sucrose during Phase III of berry development [95]. However, the increase in sucrose synthase during Phase III of berry development indicates that this isogene may participate in the catabolism of sucrose to fructose and glucose. Alternatively, this sucrose synthase isogene may play a critical role in cellulose synthesis associated with Phase III cell expansion similar to its role in cotton fiber elongation [98]. Two cellulose synthase isogenes (1607069_at, TC53461; 1611149_at, TC56091) displayed increased transcript abundance during Phase II and III, consistent with this hypothesis (see Table 1). Additional developmentally regulated transcripts related to carbohydrate metabolism and transport are summarized in Table 6.
Table 6

Transcripts (TFR pool) related to carbohydrate metabolism and transport categorized by the first hit in the MIPS2 catalog

Probeset ID

GenBank Annotation

VvGI5

UniProt ID

Gene Name Description

Function

Profile

Fold Change

1618061_a_at

CF514699

TC52548

O78327

Transketolase

Amino Acids Metabolism

20

3.44

1614105_at

CB968800

TC70460

Q4JIY3

Pyruvate dehydrogenase

Amino Acids Metabolism

11

2.2

1616700_at

CB910092

TC53526

Q9SLY2

Sucrose synthase

Carbohydrate metabolism

3

227.67

1611613_at

BQ796771

TC60693

Q9S944

Invertase

Carbohydrate metabolism

3

61.86

1622656_at

CF215745

TC61716

Q5NA70

Glucan endo-1,3-b-glucosidase

Carbohydrate metabolism

2

53.85

1614716_at

CB978853

TC58640

Q6Z8F4

Phosphoribulokinase

Carbohydrate metabolism

12

51.76

1617719_at

CB975632

TC55314

Q6IV07

UDP-glucose:protein transglucosylase

Carbohydrate metabolism

2

40.93

1607442_at

CF403717

-

Q50HW0

Glucuronosyltransferase

Carbohydrate metabolism

2

38.54

1622115_at

CD004218

TC60627

Q9SRX8

b-glucosidase

Carbohydrate metabolism

10

26.34

1611970_at

CF207195

TC62847

Q9LKY6

Glucose acyltransferase

Carbohydrate metabolism

3

25.74

1620679_at

CB972076

TC53351

Q9LV33

b-glucosidase

Carbohydrate metabolism

14

16.26

1621352_at

BQ794457

TC59789

Q8GT41

Invertase inhibitor

Carbohydrate metabolism

11

16.06

1608932_at

CB982469

TC63201

Q59J80

Glucosyltransferase

Carbohydrate metabolism

11

15.38

1620347_at

CA814065

TC66065

Q5QPZ6

Glycosyltransferase

Carbohydrate metabolism

10

15.36

1622282_at

CD712313

TC54393

Q7XAE2

Fructokinase

Carbohydrate metabolism

2

13.54

1616642_at

BQ800221

TC64250

Q9FEP9

Glycerol-3-phosphate acyltransferase

Carbohydrate metabolism

16

11.07

1616255_at

CF516475

TC57339

O82616

Fructokinase

Carbohydrate metabolism

12

10.13

1612918_at

CB972844

TC52651

Q9MBD7

NAD-dependent sorbitol dehydrogenase

Carbohydrate metabolism

2

9.14

1608393_at

CF403620

TC64860

O22658

ADP-glucose pyrophosphorylase

Carbohydrate metabolism

7

8.79

1621067_at

CF511425

TC51908

Q8W3C8

Glucose acyltransferase

Carbohydrate metabolism

3

8.2

1612883_at

CB911656

TC60606

O22060

Sucrose-phosphate synthase 1

Carbohydrate metabolism

16

7.92

1617035_s_at

CF205538

TC64995

Q9XGN4

Galactinol synthase

Carbohydrate metabolism

11

7.73

1609652_s_at

CF215703

TC59328

Q9FNI7

Glucosyltransferase

Carbohydrate metabolism

3

7.5

1617309_at

CB922444

TC59505

Q8LFT7

Aldehyde dehydrogenase

Carbohydrate metabolism

10

7.26

1619190_at

CD720196

TC54797

Q6H5W0

Alcohol dehydrogenase

Carbohydrate metabolism

3

6.66

1616107_s_at

CD715446

TC67979

Q94EU9

b-amylase

Carbohydrate metabolism

9

6.34

1618409_at

CF514784

TC52918

Q94G86

Glucan endo-1,3-b-glucosidase

Carbohydrate metabolism

3

6.26

1620624_at

CB969436

TC52478

Q94IP3

UDP-Glucose Transferase

Carbohydrate metabolism

2

6.21

1611680_at

CF415491

TC58448

Q50HU7

Glycosyltransferase

Carbohydrate metabolism

2

5.8

1612465_at

CF568806

TC53602

O65736

b-galactosidase

Carbohydrate metabolism

4

5.76

1618071_at

CF518536

TC54381

Q9M8Y0

O-linked GlcNAc transferase

Carbohydrate metabolism

16

5.7

1611804_at

CF513259

TC62252

Q9ZVX4

Glucose acyltransferase

Carbohydrate metabolism

12

5.52

1617454_at

BQ798893

-

Q8VYG2

Galactokinase

Carbohydrate metabolism

2

5.43

1612836_at

CF403299

TC57719

Q9S943

Invertase

Carbohydrate metabolism

3

5.28

1618517_at

CB971627

TC53602

Q93X58

b-galactosidase

Carbohydrate metabolism

4

5.01

1622074_at

BQ794083

-

Q84JP7

Phosphoenolpyruvate carboxylase kinase

Carbohydrate metabolism

12

4.66

1615571_at

CB983156

TC53551

Q9FNF2

Starch synthase

Carbohydrate metabolism

9

4.58

1622543_at

CB977855

TC61696

Q84V96

Aldehyde dehydrogenase

Carbohydrate metabolism

1

4.57

1610724_at

CB916342

TC63651

Q652S1

Fructose/tagatose bisphosphate aldolase

Carbohydrate metabolism

11

4.57

1620997_at

CD799067

TC63159

Q84LI1

Galactose dehydrogenase

Carbohydrate metabolism

2

4.55

1619223_s_at

CB005867

TC52910

Q9SLS2

Sucrose synthase

Carbohydrate metabolism

2

4.46

1615614_at

CF405918

TC54197

Q9M3I0

Glucosyltransferase

Carbohydrate metabolism

2

4.28

1622065_at

CD801714

-

Q94FA7

Fructose-bisphosphatase

Carbohydrate metabolism

3

4.17

1622503_at

CF203022

TC69704

Q9ATW1

Mannitol dehydrogenase

Carbohydrate metabolism

1

4.16

1615634_at

CB970085

TC69016

Q8L9U9

Glucose acyltransferase

Carbohydrate metabolism

12

3.86

1607324_at

CD719348

TC54773

P94078

a-mannosidase

Carbohydrate metabolism

2

3.85

1611112_at

CB971308

TC51885

Q7XPW5

Phosphomannomutase

Carbohydrate metabolism

3

3.85

1616325_at

CF211815

TC53040

Q6Q2Z9

Phosphoenolpyruvate carboxylase

Carbohydrate metabolism

3

3.84

1617068_at

CF519166

TC54621

Q9SGX4

Water dikinase

Carbohydrate metabolism

18

3.8

1611604_at

CB916873

TC54851

Q8LPJ3

a-mannosidase

Carbohydrate metabolism

3

3.78

1620724_at

CB915307

TC66445

O48628

Phosphofructo-1-kinase

Carbohydrate metabolism

11

3.73

1616500_at

AF194175

TC52882

Q9FZ00

Alcohol dehydrogenase

Carbohydrate metabolism

10

3.69

1612870_s_at

CF201540

TC66152

Q0DAH4

GDP-4-keto-6-deoxy-D-mannose-3,5-epimerase-4-reductase

Carbohydrate metabolism

3

3.66

1608527_at

CF515950

TC58983

Q9FJ95

Sorbitol dehydrogenase

Carbohydrate metabolism

10

3.6

1619457_at

CB969731

TC63406

P93653

Trehalose-6-phosphate synthase

Carbohydrate metabolism

12

3.58

1611154_at

CF204490

-

Q42954

Pyruvate kinase

Carbohydrate metabolism

3

3.54

1614552_at

CB978862

TC54160

Q5SMZ1

Aldose 1-epimerase

Carbohydrate metabolism

12

3.52

1608263_a_at

BQ794795

TC51761

Q9M6B4

Alcohol dehydrogenase

Carbohydrate metabolism

11

3.5

1617186_at

CF415580

TC70119

O65856

Glucose-6-phosphate dehydrogenase

Carbohydrate metabolism

1

3.49

1608907_s_at

CA809004

TC51713

Q9XGN4

Galactinol synthase

Carbohydrate metabolism

11

3.4

1613182_at

CB982869

-

Q6PP98

Pyruvate dehydrogenase kinase

Carbohydrate metabolism

11

3.37

1612414_at

CD715284

TC58601

Q42910

Pyruvate phosphate dikinase

Carbohydrate metabolism

10

3.34

1622120_at

CF519014

TC54533

P27598

Starch phosphorylase

Carbohydrate metabolism

21

3.33

1606536_at

CB971452

-

Q8S9A7

Glucosyltransferase

Carbohydrate metabolism

3

3.29

1622606_at

CB910226

TC52786

Q6DW08

GDP-mannose pyrophosphorylase

Carbohydrate metabolism

3

3.28

1610766_at

CF212685

TC53291

Q7Y152

Galactokinase

Carbohydrate metabolism

11

3.24

1615270_at

CF208284

TC70917

Q6K963

Callose synthase

Carbohydrate metabolism

21

3.23

1615167_at

CF519116

TC65652

Q9LFQ0

Glycosylation enzyme

Carbohydrate metabolism

12

3.2

1606774_at

CF415165

TC70261

Q8L7J4

Pyruvate kinase

Carbohydrate metabolism

11

3.14

1609402_at

BQ794844

TC62599

Q9SLY2

Sucrose synthase

Carbohydrate metabolism

11

3.09

1608100_at

CF404013

TC51810

Q8S569

Phosphoenolpyruvate carboxylase

Carbohydrate metabolism

2

3.07

1609470_at

CF203556

-

Q8LFZ9

Sucrase

Carbohydrate metabolism

5

3.04

1614023_at

CF414667

-

P46275

Fructose-1,6-bisphosphatase

Carbohydrate metabolism

2

3.01

1618726_at

CF211103

TC60540

Q5JNJ1

Trehalose-6-phosphate synthase/phosphatase

Carbohydrate metabolism

4

3

1614982_at

CF211066

TC61602

Q9C9P3

GDP-mannose pyrophosphorylase

Carbohydrate metabolism

3

2.99

1616783_at

CF405837

TC58450

P93344

Aldehyde dehydrogenase

Carbohydrate metabolism

11

2.95

1616630_at

CF603093

TC56347

Q94LX9

Phosphoenolpyruvate carboxylase

Carbohydrate metabolism

16

2.95

1620905_at

CF215819

TC68052

Q6RK07

UDP-glucose dehydrogenase

Carbohydrate metabolism

21

2.89

1621861_at

CF209183

TC65564

Q94AS2

b-amylase

Carbohydrate metabolism

11

2.87

1613188_at

CA817889

TC70258

Q5BLY1

a-amylase

Carbohydrate metabolism

11

2.85

1608207_at

CB343787

TC63660

Q84V96

Aldehyde dehydrogenase

Carbohydrate metabolism

3

2.7

1611808_at

CF205006

TC67979

Q94EU9

b-amylase

Carbohydrate metabolism

9

2.69

1610410_at

CB342966

TC61245

O64733

Glucosyltransferase

Carbohydrate metabolism

9

2.67

1611851_at

BQ799617

TC52022

Q9FIK0

Phosphofructo-1-kinase

Carbohydrate metabolism

10

2.67

1609545_at

CF514819

TC52560

Q4R0T9

ADP-sugar diphosphatase

Carbohydrate metabolism

11

2.64

1617368_at

CF512540

-

E1313

Glucan endo-1,3-b-glucosidase

Carbohydrate metabolism

3

2.63

1615623_at

CF511813

TC55899

O64733

Glucose acyltransferase

Carbohydrate metabolism

2

2.63

1620375_at

CA814054

TC62155

Q8LK43

Glycogene synthase kinase-like kinase

Carbohydrate metabolism

7

2.58

1613601_at

CB978458

TC67353

O64927

Starch synthase

Carbohydrate metabolism

3

2.56

1618125_at

BQ798742

-

Q94KE3

Pyruvate kinase

Carbohydrate metabolism

16

2.52

1617941_at

CB914224

TC62494

O81505

Water dikinase

Carbohydrate metabolism

11

2.52

1621073_at

CB914439

TC55380

Q7XEL0

GDP-mannose-3",5"-epimerase

Carbohydrate metabolism

3

2.51

1620165_at

CA817563

TC56014

Q84YG5

Isoamylase

Carbohydrate metabolism

11

2.51

1613060_at

CF214238

TC53819

Q9M3B6

Pyruvate kinase

Carbohydrate metabolism

18

2.51

1620904_at

CF609568

TC58209

Q9SAD5

b-1,4-N-acetylglucosaminyltransferase

Carbohydrate metabolism

16

2.49

1611027_at

CB978747

TC56057

Q3L7K5

Invertase

Carbohydrate metabolism

20

2.49

1608995_at

BQ796616

TC54941

Q84NI6

a-galactosidase

Carbohydrate metabolism

11

2.48

1622806_at

CB009073

TC63769

Q6VWJ5

Fructokinase

Carbohydrate metabolism

1

2.48

1609510_at

CF513342

TC69905

Q0WV85

O-linked GlcNAc transferase

Carbohydrate metabolism

16

2.47

1609232_at

CA811215

TC56883

Q9ZVJ5

Phosphoglucomutase

Carbohydrate metabolism

15

2.45

1613514_s_at

CF202452

TC54941

Q9M442

a-galactosidase II

Carbohydrate metabolism

11

2.44

1613025_at

CF403382

TC69507

Q9SNY3

GDP-mannose 4,6 dehydratase 1

Carbohydrate metabolism

21

2.43

1614514_at

CF405361

TC66847

Q84V39

Glucan endo-1,3-b-glucosidase

Carbohydrate metabolism

2

2.42

1608156_at

CF207998

TC58210

Q9XEY7

Trehalase

Carbohydrate metabolism

11

2.4

1612056_at

BQ795970

-

Q5BMC5

Phosphomannose isomerase

Carbohydrate metabolism

19

2.39

1612295_at

CF512417

TC67968

Q5VMJ5

Pyrophosphate-dependent phosphofructo-1-kinase

Carbohydrate metabolism

15

2.38

1609079_at

BQ796278

TC60979

Q94KE3

Pyruvate kinase

Carbohydrate metabolism

13

2.36

1615874_at

CF403960

TC54126

Q93XR7

Fructose-6-phosphate,2-kinase\/fructose-2,6-bisphosphatase

Carbohydrate metabolism

2

2.35

1608883_at

CA818676

TC60515

Q94AA4

Pyrophosphate-dependent phosphofructo-1-kinase

Carbohydrate metabolism

15

2.34

1616002_s_at

CB345569

TC52261

Q8LL68

Aldolase

Carbohydrate metabolism

3

2.29

1620865_at

CB917214

TC66899

Q7XBE4

Enolase

Carbohydrate metabolism

11

2.29

1607147_at

CF404016

-

Q5BLY0

a-amylase

Carbohydrate metabolism

10

2.28

1607727_at

CB976321

TC57680

Q5IH14

Sucrose-6-phosphate phosphatase

Carbohydrate metabolism

11

2.26

1614707_at

BQ799313

TC53692

P32811

a-glucan phosphorylase

Carbohydrate metabolism

21

2.25

1610277_at

CF208016

TC70514

Q50HW6

b-1,3-glucuronosyltransferase

Carbohydrate metabolism

2

2.25

1621432_s_at

CD005042

TC52007

Q8VXZ7

a-galactosidase

Carbohydrate metabolism

10

2.18

1621053_at

CF414284

TC63955

Q6VWJ5

Fructokinase

Carbohydrate metabolism

3

2.16

1621719_at

CF404994

TC65554

Q8LGH6

Dihydrolipoamide S-acetyltransferase

Carbohydrate metabolism

3

2.14

1619373_at

CB920390

TC69024

P80572

Alcohol dehydrogenase

Carbohydrate metabolism

3

2.13

1614612_at

CF513589

TC63370

Q9LSG3

Glucose acyltransferase

Carbohydrate metabolism

2

2.13

1615252_at

BQ792622

TC60550

Q5N8H1

Hydrolase-like protein

Carbohydrate metabolism

3

2.08

1612568_at

CF405938

TC67425

Q9LIB2

Glycogen phosphorylase B

Carbohydrate metabolism

13

2.07

1614153_at

CF207979

TC54491

Q7EYK9

Glucose-6-phosphate 1-dehydrogenase

Carbohydrate metabolism

4

2.03

1621378_at

BQ794342

TC61809

Q42581

Ribose-phosphate pyrophosphokinase 1

Nucleotide metabolism

11

4.5

1607578_at

CF415519

TC56533

O22141

Nucleotide sugar epimerase

Nucleotide metabolism

2

4.09

1608708_at

CF211873

TC53982

Q9SU83

Nucleotide pyrophosphatase

Nucleotide metabolism

18

3.73

1616669_at

CF209174

TC54382

Q3EAE2

dTDP-4-dehydrorhamnose reductase

Nucleotide metabolism

3

3.45

1609246_s_at

CF206363

TC54199

Q655Y8

UDP-glucose 4-epimerase

Nucleotide metabolism

4

3.14

1607889_a_at

CB976234

TC58106

Q6IVK4

UDP-glucuronate decarboxylase 2

Nucleotide metabolism

4

2.55

1622819_at

BQ798887

TC59368

O22141

Nucleotide sugar epimerase

Nucleotide metabolism

2

2.52

1616344_at

CF209136

TC68545

Q6XP48

UDP-glucose 4-epimerase

Nucleotide metabolism

21

2.52

1614498_at

CF213286

TC57825

O65781

UDP-galactose 4-epimerase

Nucleotide metabolism

21

2.32

1620930_s_at

CF212327

TC51843

Q6IVK4

UDP-glucuronate decarboxylase 2

Nucleotide metabolism

4

2.21

1614184_at

CF604220

TC66293

Q9SA77

UDP-galactose 4-epimerase

Nucleotide metabolism

21

2.13

1618478_at

CF515277

-

O64749

UDP-galactose-4-epimerase

Nucleotide metabolism

20

2.11

1616383_at

CF609704

TC59968

Q8L9F5

dTDP-glucose 4-6-dehydratase

Nucleotide metabolism

21

2.06

1615814_at

CB920915

TC56030

Q7FAH2

Glyceraldehyde-3-phosphate dehydrogenase

Phosphate Metabolism

10

2.87

1622715_s_at

CA809281

TC51781

P12858

Glyceraldehyde-3-phosphate dehydrogenase

Phosphate Metabolism

3

2.45

1618277_at

CF568829

TC56963

Q8VWN9

Glyceraldehyde-3-phosphate dehydrogenase

Phosphate Metabolism

21

2.22

1616083_at

CB009608

TC51694

Q9ZR63

Hexose transporter (VvHT1)

Transport

2

12.37

1610527_at

CA815926

TC52979

Q84QH3

Sorbitol transporter

Transport

2

5.49

1615257_at

CB972713

TC65400

Q4U339

Hexose transporter (VvHT6)

Transport

15

4.7

1619691_at

CF211807

TC62520

Q4U339

Hexose transporter (VvHT6)

Transport

14

3.69

1613408_at

CB347178

TC66667

P93075

Sucrose transporter (BvST1)

Transport

11

2.92

1608991_at

CA816013

TC60060

Q8GTR0

Sugar transporter

Transport

10

2.86

1610298_at

CB972367

TC53493

Q8LES0

Golgi nucleotide sugar transporter (GONST) 4

Transport

2

2.71

1615697_at

AF021810

TC51724

Q4JLW1

Sucrose transporter (VvSuc27)

Transport

3

2.44

1611331_at

CF201541

TC69532

Q69M22

Golgi nucleotide sugar transporter (GONST) 4

Transport

7

2.2

1612481_at

CF213270

-

Q6ID34

Glycerol 3-phosphate transporter

Transport

4

2.03

Hexose and triose phosphate transport

The transcript abundances of numerous hexose and triosephosphate transporters varied considerably over the course of berry development (Figure 8C) indicating that each may fulfill different transport roles. The transcript abundance for a VvHT1 (1616083_at, TC51694), a previously described hexose transporter (VvHT1) located at the sieve cell-companion cell interface in the phloem and thought to play a major role in providing energy (mainly from glucose) for cell division and cell growth during the early stages of berry development [99], was high during Phase I, but then declined rapidly during ripening; this is largely consistent with an earlier report [18]. A second hexose transporter, VvHT6 (1615257_at; TC65400) exhibited a peak in transcript abundance near the start of véraison (E-L stage 34), which correlated well with hexose accumulation in the berries (Figure 8A), indicating that this transporter may play a significant role in hexose accumulation during berry ripening. Another previously described sucrose transporter (VvSUC27; 1615697_at, TC51724) [100], exhibited decreased transcript abundance throughout berry development consistent with earlier observations.

A putative plastidic glucose transporter (1608991_at, TC60060) showed increased transcript abundance up to E-L stage 34 and then remained constant throughout berry ripening (Figure 8C). The transcript abundance of a putative plasma membrane sugar/polyol transporter (1613408_at, TC66667), which resembles the AtPLT5 gene from A. thaliana [101] and is also capable of hexose transport, increased gradually over the course of berry development. In addition, two transcripts encoding a plastidial phosphate translocator-like (PTL) protein (1619379_at, TC58801) and a plastidial triosephosphate/phosphate translocator, TPT (1622157_at, TC61733) [102] displayed similar expression patterns that peaked at E-L stage 34 and then declined with berry ripening. The observed patterns of expression of the plastidial glucose and triosephosphate transporters indicate that both glucose and triosephosphates may be mobilized as export products as a result of active starch metabolism in plastids of developing and ripening berries.

Finally, a sorbitol transporter (Figure 9) that has high homology with a cherry sorbitol transporter (PcSOT2) [103], has high transcript abundance early in fruit development as it does in cherry fruit. This transporter has high specificity for sorbitol as compared to its isomer, mannitol [103]. We were able to detect a sugar alcohol in our polar extracts using GC-MS, but were unable to distinguish whether it was sorbitol or mannitol. Further work will be done to distinguish sorbitol from mannitol. Note, however, that sorbitol has been detected in the sap of grapevines [104].

Starch metabolism

Starch metabolism in developing and ripening grape berries is poorly understood. Starch synthase I catalyzes the elongation of glucans by the addition of glucose residues from ADP-glucose through the formation of α-1,4 linkages and is a major determinant for the synthesis of transient starch reserves in plants [105]. Our data indicate that starch metabolism is significant in berries. Starch concentrations declined significantly during Phase III of berry development; E-L stage 35, 36 and 38 were equal to 774 ± 57, 715 ± 54 and 554 ± 28 μg of glucose per g fresh weight of berry, respectively (mean ± SE).

Furthermore, the transcript abundance of numerous transcripts involved in starch metabolism changed during berry development. One plastidial soluble starch synthase Unigene (1615571_at, TC53551) displayed increasing transcript abundance, while a second Unigene (1613601_at, TC67353) displayed decreasing transcript abundance during berry development (Figure 8D). A transcript for the plastidial α-glucan, water dikinase (Gwd) gene (1617941_at, TC62494), which encodes an enzyme that is a regulator of starch mobilization and is essential for starch degradation [106], showed increased accumulation during berry development much like starch synthase I (1615571_at, TC53551). A second Gwd isogene (1617068_at, TC54621), showed peak transcript expression at E-L stage 35, but declined in fully ripe berries. Expression of plastidial α-1,4 glucan phosphorylase (Starch phosphorylase L isozyme, 1622120_at, TC54533), a starch mobilization enzyme that phosphorylates amylopectin to catalyze the release of glucose-1-phosphate, was nearly coordinate with the expression of this latter Gwd isogene. Finally, transcripts encoding the starch degrading enzymes, α-amylase (1613188_at, TC70258) and β-amylase (1617124_at, TC67979), both showed increased abundance during berry development (Figure 8D). Grape berries are likely to contain intact and functional plastids at véraison and at later stages of ripeness as shown by in situ fixation of exocarp and mesocarp cells [107].

Figure 9 summarizes the major pathways of hexose sugars and polysaccharide flux and putative transport processes in the developing berry as defined by the combined transcriptomic and metabolite analyses performed in this study. Abridged gene expression patterns for key regulatory genes involved in both sucrose and starch metabolism are shown. One can easily visualize the coordinate transcript expression patterns for the entire pathway along berry development. It is not apparent from this analysis why fructose concentrations would be higher than glucose in berries. This indicates that the regulation of these hexoses by hexokinase genes, whose transcripts did not significantly change (data not shown), is more complex than what can be discerned from a simple examination of transcript profiles.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-429/MediaObjects/12864_2007_Article_1142_Fig9_HTML.jpg
Figure 9

Transcriptomic mapping of transcripts related sucrose and starch metabolism along berry development. SPS: s ucrose p hosphate s ynthase-(1614674_at, TC60623), SPP: s ucrose p hosphate p hosphorylase – (1608257_at, TC68135) SUSY: su crose sy nthase – a) (1616700_at, TC53526) b) (1619223_s_at, TC52910) c) (1609402_at, TC62599) INV: inv ertase – a) (1620628_at, TC67908) b) (1611027_at, TC56057) c) (1612836_at, TC57719) d) (1611613_at, TC60693) HK: h exok inase-(1611419_at – TC53318) FK: f ructok inase – a) (1628006_at, TC63769), b) (1622282_at, TC54393), c) (1621053_at, TC63955), d) (1616255_at, TC57339) SuT: su crose t ransporter – a) (1620256_at, AF021808) b) (1622221_at, AF021809) c) (1615697_at, TC51724) d) (1615257_at, TC65400) NPP: n ucleotide p yrop hosphatase – (1620770_at, TC53085) SDH: s orbitol d eh ydrogenase – (1608527_at, TC58983) ST: s orbitol t ransporter – (1610527_at, TC52979) AGPase: A DP-g lucose p hosphatase – a) (1608393_at, TC64860) b) (1610928_at, TC64860) SBE: s tarch b ranching e nzyme – (1621790_at, TC65671) SS: s tarch s ynthase – a) (1615571_at, TC53551) b) (1613601_at, TC67353) SP: s tarch p hosphorylase – a) (1622120_at, TC54533) b) (1614707_at, TC53692) α AM: α-am ylase – (1613188_at, TC70258) β AM: β-am ylase – a) (1617124_at, TC67979) b) (1611808_at, CF205006) SEX: water dikinase – (1617941_at, TC62494) TPT: t riose p hosphate t ransporter – a) (1608991_at, TC60060) b) (1619379_at, TC58801) c) (1622157_at, TC61733). Each square from left to right corresponds to the expression of the probe sets from stage 31 through stage 38. Nonsignificant: Does not pass the ANOVA filter.

Photosynthesis and carbon assimilation

During berry development transcripts encoding proteins associated with photosynthesis-related functions are strongly expressed during the flowering stage and the so-called "herbaceous phase" or Phase I of berry development with expression declining during the later stages of berry maturation [17, 18]. In our data, around 100 Unigenes with photosynthesis-related functions were identified with most displaying a steady or transient decline in the transcript abundance across berry development (Additional file 5, Table 7). Similarly, transcripts encoding enzymes with roles in carbon assimilation also exhibited a declining pattern of expression. For instance, Unigenes encoding Calvin cycle enzymes such as glyceraldehyde-3-phosphate dehydrogenase (1615814_at, TC56030; 1622715_s-at, TC51781), phosphoribulokinase (1614716_at, TC58640), transketolase (1618061_a_at, TC52548) as well as ribulose biphosphate carboxylase/oxygenase small subunit (1612848_x_at, TC64044) were highly expressed and then declined during Phase III of berry development consistent with previous reports [18].
Table 7

Transcripts (TFR pool) related to Energy metabolism within specific sub-sections

Probeset ID

GenBank Annotation

VvGI5

Uniprot ID

Gene Name Description

Function

Profile

Fold Change

1612882_at

CD720949

TC64621

A5BS41

ATP-dependent transmembrane transporter

ATP binding

2

5.55

1612645_at

CB344170

TC55708

P32980

ATP synthase

ATP binding

3

3.59

1616533_at

CB339497

TC62259

P31853

ATP synthase B' chain

ATP binding

12

2.88

1618182_at

CF604629

TC63054

P19023

ATP synthase beta chain

ATP binding

21

2.23

1607759_at

CD798264

TC67523

Q43433

Vacuolar ATP synthase subunit B isoform 2

ATP binding

11

2.16

1620500_at

CB349662

CB349662

Q67IU5

Ribulose 1,5-bisphosphate carboxylase small subunit

Carbon dioxide fixation

3

19.73

1613936_x_at

CF568996

CF568996

O22077

Ribulose bisphosphate carboxylase small chain

Carbon dioxide fixation

3

2.36

1616918_s_at

CB345541

TC56391

Q40281

Rubisco activase

Carbon dioxide fixation

3

2.22

1619681_at

CD799678

TC70996

Q9C5C7

Rubisco expression protein

Carbon dioxide fixation

11

2.18

1612848_x_at

CF202280

CF202280

P10795

Ribulose bisphosphate carboxylase

Carbon dioxide fixation

3

2.13

1620551_s_at

CB339855

TC56836

O98997

Rubisco activase

Carbon dioxide fixation

3

2.13

1610491_at

CD010750

TC57419

Q8LF17

Ribulose-1,5-bisphosphate carboxylase/oxygenase

Carbon dioxide fixation

12

2.13

1616847_s_at

CA816751

TC68454

O22077

Ribulose bisphosphate carboxylase small chain

Carbon dioxide fixation

3

2.12

1616435_at

CB974220

TC68219

P08927

RuBisCO subunit binding-protein beta subunit

Carbon dioxide fixation

3

2.1

1622299_s_at

CK136935

CK136935

Q9LKH8

NADPH-protochlorophyllide oxidoreductase

Chlorophyll biosynthesis

3

5.3

1619717_at

CF210684

TC59048

Q9SDT1

NADPH:protochlorophyllide oxidoreductase

Chlorophyll biosynthesis

3

4.79

1606624_at

CF606923

TC64589

Q43082

Porphobilinogen deaminase

Chlorophyll biosynthetic process

1

2.5

1617935_at

CB974545

TC68056

Q7YJS8

NADH dehydrogenase 49kDa subunit

Complex 1

16

5.55

1611418_at

CB342953

TC56161

Q7YJ08

NAD(P)H-quinone oxidoreductase

Complex 1

14

5.09

1609373_at

CD800734

TC60468

Q6KGY1

NADH dehydrogenase

Complex 1

14

3.05

1614095_at

CF606244

TC62268

P06261

NAD(P)H-quinone oxidoreductase

Complex 1

21

2.83

1609421_at

BQ795266

TC62811

O65414

NADH dehydrogenase

Complex 1

11

2.75

1617757_at

CA818465

TC58524

Q6YSN0

NADH dehydrogenase

Complex 1

21

2.42

1612005_s_at

CB004075

TC64671

Q68S01

NADH dehydrogenase

Complex 1

3

2.27

1610869_at

CF515388

TC56269

Q8H2T7

NADH dehydrogenase subunit

Complex 1

16

2.23

1610347_s_at

CF202826

CF202826

Q0ZIW2

NAD(P)H-quinone oxidoreductase

Complex 1

10

2.1

1609391_s_at

CF404650

TC53103

Q41001

Copper Binding Protein

Copper ion binding

2

26.11

1620588_at

CD801157

CD801157

Q8LED5

Mavicyanin

Copper ion binding

6

25.27

1621220_at

CB919187

TC59624

Q9M510

Dicyanin

Copper ion binding

11

17.36

1610220_at

CB973621

TC68272

O81500

Copper Binding Protein

Copper ion binding

3

14.36

1617350_at

CB975555

TC58747

Q39131

Copper Binding Protein

Copper ion binding

3

10.21

1611332_at

CF371813

TC59560

Q653S5

Blue copper binding protein (bcb)

Copper ion binding

1

7.64

1607270_at

CB923224

TC60083

Q9ZRV5

Copper Binding Protein

Copper ion binding

2

5.87

1620744_at

CF403966

TC65998

P17340

Plastocyanin, chloroplast precursor

Copper ion binding

3

4.41

1617046_at

CF512505

TC54856

O23230

Trichohyalin

Copper ion binding

3

2.23

1609233_at

CF512410

TC54170

Q84RM1

Copper Binding Protein

Copper ion binding

2

2.21

1618207_at

CB347324

TC52865

Q9C540

Cytochrome 561

Electron carrier activity

3

7.45

1612624_at

CB974055

TC58854

P06449

Apocytochrome f

Electron carrier activity

21

5.32

1611598_at

CB970208

TC60594

Q9ZSR3

Cytochrome b-561

Electron carrier activity

2

4.54

1606617_at

CF608010

TC65350

O23344

Electron transport

electron carrier activity

3

2.49

1606704_s_at

CF200937

CF200937

P59702

Cytochrome b559 alpha subunit

Electron carrier activity

21

2.33

1615927_s_at

CB972155

TC55109

Q6Q8B8

Chloroplast ferredoxin I

Electron carrier activity

3

2.23

1607800_at

CB972521

TC52149

Q84WN3

Cytochrome c oxidoreductase

Electron transport

2

17.79

1620504_at

CB342755

TC52829

Q84WN3

cytochrome c oxidoreductase

Electron transport

7

14.78

1618535_at

CA818656

CA818656

Q6V5G1

Cu2+ plastocyanin

Electron transport

13

6.25

1615046_at

CF210436

TC59116

P41346

Ferredoxin--NADP reductase

Electron transport

3

5.61

1614266_at

BQ792322

TC57184

Q49KU9

Cytochrome c heme attachment protein

Electron transport

16

4.17

1613158_at

CB349843

CB349843

O47437

Cytochrome c oxidase

Electron transport

16

3.56

1612766_s_at

CF569219

CF569219

Q5PY86

NADH-cytochrome b5 reductase

Electron Transport

3

3.32

1619756_at

CB003378

TC59085

Q9LYC6

Glutaredoxin

Electron transport

14

2.88

1620991_at

CB344999

TC58191

O24068

Cytochrome oxidase subunit 3

Electron transport

16

2.26

1606445_a_at

CF512668

TC62694

P26291

Cytochrome B6-F complex iron-sulfur subuni

Electron transport

3

2.16

1608372_at

CF208491

TC51964

Q6K7S7

Cytochrome c biogenesis

Electron transport

9

2.1

1621402_a_at

CF213496

TC53161

P00051

Cytochrome c

Electron transport

11

2.01

1607356_at

CB911288

TC67262

Q8LCF6

Hypothetical Protein

ENERGY

11

12.28

1611972_s_at

CF519112

TC53292

A4X6H5

Cytochrome b

ENERGY

3

11.63

1615762_at

CD798079

TC66865

O80763

Hypothetical Protein

ENERGY

10

4.82

1616241_at

CD797326

CD797326

Q8VYC5

Hypothetical Protein

ENERGY

16

4.08

1609285_at

CF414528

TC57440

Q9FFT2

Hypothetical Protein

ENERGY

2

3.44

1611820_at

CB914713

TC69253

O80763

Hypothetical Protein

ENERGY

3

3.09

1606562_at

CF404246

TC59415

A3J369

Nitrilase 1

ENERGY

11

3.04

1621817_at

CB978007

TC64650

O80763

Hypothetical Protein

ENERGY

3

3

1614875_at

CF518552

TC69033

A5AU55

Hypothetical Protein

ENERGY

11

2.73

1622517_at

CB970523

TC54809

Q8W4Z5

Hypothetical Protein

ENERGY

3

2.39

1621903_at

CF404558

TC62294

Q9FE29

Hypothetical Protein

ENERGY

13

2.23

1612648_at

CD798203

CD798203

O80763

Hypothetical Protein

ENERGY

21

2.15

1622345_at

CB970837

TC55633

Q7XTZ0

Mandelonitrile lyase

Flavoprotein

2

4.87

1606948_at

CF404230

CF404230

Q01JW7

Mandelonitrile lyase

Flavoprotein

2

3.68

1622745_at

BQ796736

TC58626

Q8L5Q7

Quinone oxidoreductase

FMN binding

15

19.63

1615481_at

CB973026

TC62178

Q9ZSP7

Cytochrome b5 DIF-F

Iron ion binding

3

2.57

1606727_at

BQ799998

TC62672

Q58IV4

Phytochrome C

Light Signaling

10

2.38

1617604_at

CF609932

TC59809

Q94BM7

Phytochrome A supressor spa1 protein

Light Signaling

11

2.25

1611135_at

CB983077

TC51911

Q9SG92

Alpha-hydroxynitrile lyase

Lyase activity

11

2.92

1622108_at

CF405863

TC56579

Q9SU40

Monocopper oxidase

Multicopper oxidase family

3

23.07

1621115_at

CF609165

TC64136

Q9SU40

Monocopper oxidase

Multicopper oxidase family

1

20.1

1617992_a_at

CF213671

TC60094

P51132

Ubiquinol--cytochrome-c reductase-like protein

Oxidative Phosphorespiration

11

2.18

1611597_at

CB918250

CB918250

Q8LDU4

Red chlorophyll catabolite reductase

Oxidoreductase activity

12

2.03

1613786_at

CD714955

TC57282

Q6QY10

P700 chlorophyll a apoprotein A1

Photosystem I

21

8.65

1611364_at

CF211293

TC52528

Q9XQB4

Reaction center subunit III

Photosystem I

3

7.67

1611464_at

CF215949

TC59235

Q9XF85

Lhca5 protein

Photosystem I

3

7.21

1621532_at

CB973721

TC64270

Q84QE6

Reaction center subunit X psaK

Photosystem I

3

7.15

1619903_at

CD720479

TC65556

Q40512

Light-harvesting chlorophyll a/b-binding protein

Photosystem I

3

6.96

1619629_at

CB340944

TC66352

Q5DNZ6

Chlorophyll a-b binding protein

Photosystem I

3

6.59

1622534_at

BQ799942

TC53444

Q84U30

Photosystem I-N subunit

Photosystem I

3

6.45

1611733_s_at

BQ797982

TC52546

Q70PN9

Reaction centre PSI-D subunit precursor

Photosystem I

3

6.44

1616560_at

CA817733

TC62550

Q84WT1

Light-harvesting chlorophyll a/b binding protein

Photosystem I

3

5.9

1611515_s_at

CB343423

TC57304

O65101

Reaction center subunit VI

Photosystem I

3

5.33

1618370_at

CF510718

TC57721

Q9SUI4

Reaction center subunit XI

Photosystem I

3

5.31

1617771_at

CF414158

TC58342

Q8RVJ8

Reaction centre subunit IV

Photosystem I

3

4.87

1618127_at

CB968637

TC62932

Q9SY97

Chlorophyll a/b-binding protein

Photosystem I

3

4.74

1614409_at

CA817387

TC55189

P13869

Chlorophyll a-b binding protein

Photosystem I

3

4.65

1614593_at

CF511805

TC52379

Q00321

CP29 polypeptide

Photosystem I

3

4.43

1611924_at

CA817406

TC63702

Q646H3

Reaction center V

Photosystem I

3

4.06

1611161_at

CF210442

TC54044

Q9ZU86

Expressed protein

Photosystem I

3

3.09

1622302_s_at

CF207602

TC54765

Q40459

Oxygen-evolving enhancer protein 1

Photosystem I

3

2.8

1610245_at

CF209798

TC53968

Q41424

Chlorophyll a/b binding protein

Photosystem II

3

15.82

1615822_at

CF208321

TC52049

Q9XQB1

LHCII type III chlorophyll a/b binding protein

Photosystem II

3

10.43

1608311_at

CF202519

CF202519

Q7M1K9

Chlorophyll a/b-binding protein

Photosystem II

3

10.24

1616940_s_at

CB348709

TC52113

Q7M1K9

Chlorophyll a/b-binding protein

Photosystem II

3

9.95

1618116_s_at

BQ798823

TC55659

Q32291

Chlorophyll A/B binding protein precursor

Photosystem II

3

7.28

1611860_at

CF209952

TC57521

Q9XQB6

Chlorophyll a/b-binding protein CP24

Photosystem II

3

6.6

1612085_at

CF413799

TC54542

Q41387

Reaction center W protein

Photosystem II

3

5.79

1621038_at

CF372077

TC57214

O64448

Light harvesting chlorophyll a/b-binding protein precursor

Photosystem II

3

5.77

1618679_s_at

CB343106

TC52042

Q9BBT1

44 kDa reaction center protein

Photosystem II

16

5.41

1610203_at

CD009386

TC56267

Q7YJY8

Photosystem Q(B) protein

Photosystem II

21

5.11

1613991_at

CF510955

TC53743

P80470

Core complex proteins psbY

Photosystem II

3

4.77

1607516_at

CB972913

TC53930

Q9LRC4

Oxygen evolving enhancer protein 1 precursor

Photosystem II

3

4.66

1613428_at

CF207158

TC52084

Q5PYQ5

Chloroplast oxygen-evolving enhancer protein

Photosystem II

3

4.47

1607961_at

CF415716

TC57429

P31336

5 kDa protein

Photosystem II

3

4.16

1614598_at

CF373065

TC61762

Q9XQB2

Chlorophyll a/b binding protein CP29

Photosystem II

3

4.06

1613691_s_at

CF511746

TC54828

P27518

Chlorophyll a-b binding protein 151

Photosystem II

3

3.84

1613773_s_at

BQ799145

TC63656

Q41387

Reaction center W protein

Photosystem II

3

3.34

1618031_s_at

CF404451

TC53833

Q8GV53

10 kDa protein

Photosystem II

3

3.28

1621351_s_at

CB340283

TC53732

Q40961

Light-harvesting chlorophyll a/b-binding protein precursor

Photosystem II

3

3.2

1613494_s_at

CA813944

TC55522

Q9SLQ8

Oxygen-evolving enhancer protein 2

Photosystem II

3

3.05

1617605_at

CF513977

TC55526

Q8HS34

CP47 protein

Photosystem II

18

2.99

1618274_at

CB972471

TC55538

Q4FFQ9

Phosphoprotein

Photosystem II

21

2.92

1610144_at

CB342508

TC53591

Q9MTN0

Uncharacterized 6.9 kDa protein in psbD-trnT intergenic region

Photosystem II

15

2.88

1611582_s_at

CB970190

TC70959

Q02060

22 kDa protein

Photosystem II

3

2.69

1607926_at

CF202256

CF202256

Q9AR57

Putative membrane protein

Photosystem II

2

2.56

1621978_at

CB837910

TC56626

Q9M3M7

Uncharacterized protein

Photosystem II

16

2.31

1607803_at

CB975690

TC52112

Q06364

26S proteasome non-ATPase regulatory subunit 3

Photosystem II

21

2.31

1619523_at

CB969438

TC67627

Q952R1

Succinate dehydrogenase

Succinate dehydrogenase activity

15

2.24

Circadian cycles

Circadian clocks are signaling networks that enhance an organism's growth, survival, and competitive advantage in rhythmic day/night environments [108]. The plant circadian clock modulates a wide range of physiological and biochemical events, such as stomatal and organ movements, photosynthesis and induction of flowering. A model of circadian rhythm based upon activities of several enzymes has been created involving transcription factors such as CIRCADIAN CLOCK-ASSOCIATED 1 (CCA1) or pseudo-response regulators such as PRR7 [108]. Transcripts for Unigene (1616834_at, TC54726) encoding CCA1 were repressed during the early stages of berry development, but increased in abundance at E-L stage 36. In contrast, one Unigene (1608006_at, TC51808) related to the two-component response regulator APRR7 had a transient peak of expression in the early stages of berry development. This result is consistent with the position and function of these proteins in the circadian clock. Indeed, APRR7 represses CCA1 activity in Arabidopsis thaliana. In grape, these correlations in the transcript abundance indicate the operation of the circadian clock machinery throughout berry development. In addition, those genes are thought to enhance starch mobilization, consistent with previous observations made during Phase III of berry development [109].

Pathogen and disease resistance related proteins

Pathogen-related (PR) proteins are the most abundant class of proteins present in wine and can negatively affect the clarity and stability of wine [110]. During berry development, PR genes are expressed highly throughout various stages of berry growth. Around 30 Unigenes encoding different classes of PR genes were identified with a two-fold ratio or greater expression change (Additional file 5, Table 8). Interestingly, four Unigenes encoding PR1 protein were highly expressed during early berry development, but then declined for the remainder of berry development. PR1 protein is regarded as one of the main down-stream responses of the salicylic acid signaling that plays an important role in Systemic Acquired Resistance. Salycylic acid is thought to accumulate just before véraison, which correlates well with the PR1 mRNA and protein expression [111]. The two main PR proteins that have a significant role in the defense against invading fungal pathogens are β-1,3-glucanase (PR2) and chitinase (PR3) [112]. Five Unigenes encoding β-1,3-glucanase were transiently expressed at different periods of berry development. Unigenes encoding various chitinases were also identified that displayed similar mRNA expression patterns. Some chitinase genes exhibit strong homologies with a chitinase previously observed in grape berry [111]. Another PR protein, which may play a role in grape berry defense, is thaumatin protein (PR5) [113]. Eight Unigenes encoding PR5 proteins were identified and their respective expression patterns span all stages of berry development. Taken together, the expression patterns revealed that these defense-related gene products and enzymes are expressed across all stages of berry development. Such a Systemic Acquired Resistance strategy probably minimizes pathogen invasion as previously suggested [114].
Table 8

Transcripts (TFR pool) related to Pathogenesis-Related proteins within specific sub-sections

Probeset ID

GenBank Annotation

VvGI5

Uniprot ID

Gene Name Description

Category

Profile

Fold Change

1613471_at

CF215857

TC59306

Q9SW05

Pathogenesis-related protein

PR1

3

7.83

1611058_at

CA814153

TC67060

Q7XAJ6

Pathogenesis related protein 1

PR1

3

5.76

1613816_x_at

CF074673

TC56938

Q7XAJ6

Pathogenesis related protein 1

PR1

21

4.74

1618533_at

CB970020

TC55782

Q40374

Pathogenesis related protein 1

PR1

2

2.31

1615595_at

AF239617

AF239617

Q9M563

β-1,3-glucanase

PR2

11

10.99

1620496_at

CF214365

TC66187

Q8VY12

β-1,3-glucanase

PR2

15

2.3

1608203_at

CF511734

TC64974

Q94EN5

β-1,3-glucanase

PR2

2

2.17

1616183_at

CF405742

TC62849

Q94G86

β-1,3-glucanase

PR2

14

2.17

1610324_a_at

CB346041

TC67051

Q8L868

β-1,3-glucanase

PR2

12

2.05

1621319_s_at

CB981122

TC70080

Q7XAU6

Chitinase IV

PR3

10

299.34

1613461_s_at

AF532966

AF532966

Q7XAU6

Chitinase IV

PR3

10

162.58

1607557_at

CF202548

CF202548

Q7XAU6

Chitinase IV

PR3

10

149.38

1614551_at

CB343715

TC51734

Q6JX04

Chitinase

PR3

2

49.79

1616064_at

CF205270

CF205270

O24531

Chitinase IV

PR3

11

20.19

1621583_at

CF404733

TC62834

Q6JX04

Chitinase

PR3

1

4.93

1620111_at

CF568854

CF568854

Q6JX04

Chitinase

PR3

2

3.36

1606625_at

CF603972

TC64563

Q7XB39

Chitinase IV

PR3

19

3.21

1620518_at

CF201341

CF201341

O81228

Pathogenesis related protein 4

PR4

15

43.11

1618835_s_at

BQ797163

TC58333

O81228

Pathogenesis related protein 5

PR4

15

25.9

1612160_at

CF415249

TC64611

P50699

Thaumatin

PR5

3

34.49

1618871_at

CF510551

TC55284

Q82L96

Thaumatin

PR5

3

15.65

1616617_at

AF195654

AF195654

Q9SNY0

Thaumatin

PR5

11

11.86

1607225_at

CB914105

TC65548

O65638

Thaumatin

PR5

11

8.51

1614746_at

CF214284

TC53053

Q7XST4

Thaumatin

PR5

2

5.27

1607708_at

CF413841

TC63177

Q9LZL8

Thaumatin

PR5

2

4.22

1606517_at

CB347191

TC62530

Q8LBL4

Thaumatin-like protein

PR5

14

3.51

1622374_at

CB920589

TC56535

Q41350

Thaumatin

PR5

2

3.34

1613999_x_at

CF202364

CF202364

Q84S31

Chitinase III

PR8

2

4.57

Quantitative real-time RT-PCR

To validate expression profiles obtained using the Affymetrix GeneChip® Vitis genome array, quantitative real-time RT-PCR was performed on 11 genes using gene-specific primers [Additional file 5, Table 3]. Transcript abundance patterns were calculated along the entire course of berry development. Linear regression ([microarray value] = a[RT-PCR value]+b) analysis showed an overall correlation coefficient of 0.94 indicating a good correlation between transcript abundance assessed by real-time RT-PCR and the expression profiles obtained with the GeneChip® genome arrays (Figure 10).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-8-429/MediaObjects/12864_2007_Article_1142_Fig10_HTML.jpg
Figure 10

Quantitative real-time RT-PCR of eleven transcripts. Comparison between the gene expression ratios reported by the Affymetrix GeneChip® genome array and by real-time RT-PCR. Data were from 11 probe sets across seven developmental stages. The difference in the number of PCR cycles required to produce the same amount of product is plotted against the log2 expression ratio averaged over the first time point. The linear regression line was constrained to pass through the origin. Grey solid square (1615402_at, TC56083)-ferulate-5-hydroxylase, Apricot solid triangle (1606794_at, TC63891)-osmotin precursor, red solid triangle (1616700_at, TC53526)-sucrose synthase, orange solid diamond (1607760_at, TC51695) flavonoid-3'5'-hydroxylase, light green solid round (1611650_at, TC57228)-WRKY7, dark green open square (1616880_at, TC54034)-cinnamoyl alcohol dehydrogenase, dark blue open triangle (1613896_at, TC62182)-nitrate/chloride transporter), blue open triangle (1615722_s_at, TC51776)-aquaporin PIP1.1, lavender open diamond (1611342_at, TC55943)-serine/threonine kinase, pink open circle (1612132_s_at, TC68311)-protein phosphatase 2C, brown cross (1614931_at, TC61058)-MYB transcription factor.

Conclusion

Our large-scale transcriptomic analysis demonstrated that nearly a third (28%) of genes expressed in berries exhibited at least two-fold or greater change in steady-state transcript abundance over the course of seven stages of grape berry development. Approximately two-thirds (64%) of these Unigenes could be assigned a functional annotation with the remaining one-third having obscure or unknown functions. Twenty distinct patterns of expression were resolved in order to illustrate the complex transcriptional regulatory hierarchies that exist to orchestrate the dynamic metabolic, transport, and control processes occurring in developing berries. We provided evidence that phytohormone biosynthesis and responses, particularly for ABA, ethylene, brassinosteroids, and auxins, as well as calcium homeostasis, transport, and signaling processes play critical roles in this developmental process. We also demonstrate that the expression and regulation of genes involved in cell wall biosynthesis and expansion, as well as genes involved in the biosynthesis, transport, and regulation of the phenylpropanoid and flavonoid pathways undergo dynamic changes throughout the course of berry development. Our analysis has revealed candidate genes that may participate in the production of different classes of aroma producing compounds. We have also demonstrated coordinate regulation of transcripts and the accumulation of key metabolites including tartrate, malate, and proline during berry development. A close examination of the behavior of gene expression patterns of genes involved in sugar and starch metabolism indicate that plastidial starch reserves are mobilized to fuel the production of hexose sugars during the ripening and maturation phase (Phase III) of berry development. Finally, our findings provide the first functional genomic information for hundreds of genes with obscure functions that can be exploited for hypothesis testing by traditional functional assays to improve our understanding of the complex developmental processes present in grape berries and to ultimately utilize this information to improve quality traits of wine grapes.

Methods

Plant Materials

Six twenty-year-old Cabernet Sauvignon (Vitis vinifera L.) vines grown on St. George rootstock were used during 2004 for this study. The vines were located at the Shenandoah Vineyard in Plymouth, CA, on a hillside row located in the middle of the vineyard. All plants were equipped with a drip irrigation system and watered daily to keep their water status high. Mid-day stem water potentials were measured weekly with a pressure chamber on two mature leaves per plant for a total of 6 vines [115]. For each measurement, a single leaf per plant was tightly zipped in a plastic bag to eliminate transpiration and covered with aluminum foil to deflect light and heat. After two hours of equilibration time, the petiole was cleanly cut and carefully threaded through a rubber gasket in the lid of a pressure chamber (3005 Plant Water Status Console, Soilmoisture Equipment Corp., Santa Barbara, CA, USA). The foil was removed before sealing the bagged leaf in the chamber. The balancing pressure required to visibly push stem xylem sap to the cut surface was recorded.

Two grape clusters were sampled weekly from each plant (n = 6), one from the south (sunny) and one from the north (shady) side of the plant. The clusters were pooled together for each plant in order to avoid light and temperature effects. Berry development was characterized by monitoring berry diameter, total soluble solids and titratable acidity. The berry diameter was measured with a micrometer for fifteen randomly selected berries per each of two clusters and an average berry size was computed per vine (n = 6). Total soluble solids (°Brix) were assayed (two technical replicates) with a refractometer (BRIX30, USA) from juice crushed from harvested berries from two clusters per vine (n = 6) to estimate total sugar content. Titratable acidity (g/L) of the grape juice was measured by titration to an endpoint of pH 8.4 with a strong base. The same number of repetitions as in °Brix measurements was used.

RNA extraction and microarray hybridization

Total RNA was extracted from berries finely ground in liquid nitrogen using Qiagen RNeasy Plant MidiKit columns (Qiagen Inc., CA) as previously described [116]. The total RNA was further purified using a Qiagen RNeasy Plant Mini Kit (Qiagen, Valencia, CA) according to the manufacturers' instructions. RNA integrity was confirmed by electrophoresis on 1.5% agarose gels containing formaldehyde and quality was confirmed by analysis on an Agilent 2100 Bioanalyzer using RNA LabChip® assays according to the manufacturer's instructions. mRNAs were converted to cDNAs using oligo dT primer containing a T7 RNA polymerase promoter sequence and reverse transcriptase. Biotinylated complementary RNAs (cRNAs) were synthesized in vitro using T7 RNA polymerase in the presence of biotin-labeled UTP/CTP, purified, fragmented and hybridized in the GeneChip® Vitis vinifera Genome Array cartridge (Affymetrix®, Santa Clara, CA). The hybridized arrays were washed and stained with streptavidin phycoerythrin and biotinylated anti-streptavidin antibody using an Affymetrix Fluidics Station 400. Microarrays were scanned using a Hewlett-Packard GeneArray® Scanner and image data was collected and processed on a GeneChip® workstation using Affymetrix® GCOS software.

Microarray data processing

Three biological replicates per experiment were processed to evaluate intra-specific variability. Expression data were processed by RMA (Robust Multi-Array Average) [117] using the R package affy [118]. Specifically, the RMA model of probe-specific background correction was first applied to the PM (perfect match) probes. These corrected probe values were normalized via quantile normalization and a median polish method was applied to compute one expression measure from all probe values. Data quality was verified by digestion curves describing trends in RNA degradation between the 5' end and the 3' end in each probe set. Differentially expressed genes throughout berry development were determined by ANOVA on the RMA expression values [118]. A multiple testing correction [22] was applied to the p-values of the F-statistics to adjust the false discovery rate. Genes with adjusted p-values < 0.05 were extracted for further analysis. Genes having a two-fold ratio (TFR) or greater between at least two time points along berry development were selected for further analyses. The RMA expression data (experiment Vv5) have been deposited in PLEXdb [119].

Microarray data analysis

Clustering of co-regulated genes was performed using the MultiExperimentViewer software part of the TM4 software package (MEV3.1) developed by TIGR [120]. TFR Unigenes were clustered via the Pavlidis Template Matching (PTM) algorithm [24]. The twenty template profiles were selected (by us) as representatives of biological processes occurring during berry development (Additional File 4). The Pearson correlation coefficient between each Unigene and each template profile was used to determine cluster membership: correlation measures greater than 0.75 corresponded to a good match. If genes were well correlated with more than one template profile, the gene was assigned to the cluster with which it had greatest correlation. The p-values associated to the hypothesis test of each correlation coefficient (null hypothesis is that the correlation is zero) were calculated and a multiple testing correction (Benjamini and Hochberg) was applied. Only genes with adjusted p-values ≤ 0.05 and correlations greater than 0.75 were placed into clusters

Unigene Annotation and Functional Analysis

Unigene annotation was updated by nucleotide sequence query of the probe consensus sequence against the UniProt/TrEMBL, NCBI-nr and TAIR protein databases using BLASTX (e-value < 1e-05). Functional categories were assigned automatically by amino acid homology to Arabidopsis thaliana proteins categorized according to the Munich Information Center for Protein Sequences (MIPS) Funcat 2 classification scheme [25]. Bibliographic searches were performed to assign functions to Unigenes exhibiting no homology with Arabidopsis thaliana proteins. Some annotation presented here will be subject to error due to the relatively correlative nature of these associations. It is expected that the annotated data presented here will be used for future hypothesis-driven research that can establish stronger functional analyses and annotations.

Attribution of the 20 clusters to the key developmental phases (I, II or III) (See Figure 6) was decided according to two criteria. The first one was to fit these phases with the time points used in this study. Stage 31 (Modified E-L System) was the only one belonging to the herbaceous phase (Phase I). The lag phase (Phase II) corresponded to stages 32 to 34. The maturation phase (Phase III) included stages 35 to 38. The second criterion was based on the time point at which the maximum average gene expression value was observed across the genes within each cluster. For instance, cluster 1 was included in the Phase I group, because the maximum average expression level was observed at stage 31. The same assignments were made in the other phases (II and III) (See Additional File 5: Table 1). To test for significant differences in the representation of Unigenes within each functional category per developmental phase (Phases I, II and III; see Figure 5), a Pearson's chi-squared test was used [121]. Three comparisons (Phase I against II; I against III and II against III) were performed and results are listed in Additional File 5: Table 2. Differences in frequency for each category between two stages were considered significant for a p-value < 0.05.

Real Time PCR experiments

RNA was extracted and its integrity verified by standard procedures. cDNA was synthesized using an iScript cDNA Synthesis Kit (Bio-Rad Laboratories, Hercules, CA) according to the manufacturer's instructions with a uniform 1 μg RNA per reaction volume reverse-transcribed. Primers for genes (Additional File 5: Table 3) assayed by real-time PCR were selected using Primer3 software [122]. Quantitative real-time PCR reactions were prepared using an iTaq SYBR Green Supermix with ROX (Bio-Rad) and performed using the ABI PRISM® 7000 Sequence Detection System (Applied Biosystems, Foster City, CA). Expression was determined for triplicate biological replicates by use of serial dilution cDNA standard curves per gene. In order to assess the performance of the array in a biological context, we examined the transcript abundance of some candidate genes from Cabernet Sauvignon exhibiting changing expression patterns across the 7 time points of berry development. Real-time RT-PCR was performed with the ABI PRISM® 7000 Sequence Detection System (Applied Biosystems, Forster City, CA) under annealing conditions of 50°C for 1 minute and analyzed with ABI PRISM® 7000 SDS software. Analysis of relative gene expression was performed using the 2 Δ Δ C T MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGacaGaaiaabeqaaeqabiWaaaGcbaGaeGOmaiZaaWbaaSqabeaacqGHsislcqqHuoarcqqHuoarcqqGdbWqdaWgaaadbaGaemivaqfabeaaaaaaaa@3316@ method [123]. The data were analyzed using the equation ΔΔC T = (CT,Target - CT,HG) Time X - (CT,Target - CT,HG) Time 0 where Time X is the value at any time point and Time 0 represents the 1X expression of the target gene normalized to ankyrin. Data were calculated from the calibration curve and normalized using the expression curve of an ankyrin gene (1612584_s_at; TC53110), whose mRNA presented an extremely low coefficient of variation (0.056, M Value = 0.1297) through microarray analysis [124].

Metabolite extraction and derivatization

Polar metabolites were extracted and derivatized with a water/chloroform protocol according to previously established procedures [125]. Freeze-dried berry tissue (6 mg) was placed in a standard screw-cap-threaded, glass vial. The tube was then returned to the -80°C freezer until use. Frozen tubes were wrapped in parafilm and freeze-dried overnight. All tissue samples were kept frozen throughout the lyophilization procedure. Upon lyophilization, tubes were capped and returned to the freezer until extraction. The vials were allowed to cool back to room temperature before being handled. The extraction vials were not washed with a methanol/hexane rinse, but all caps and septa were. The vial was incubated in HPLC grade chloroform for 1 hour at 50°C in an oven. A volume of Millipore water was added (m/V) containing 25 mg/L of ribitol as an internal standard and the sample was re-incubated for an additional hour at 50°C. Finally, vials were allowed to cool to room temperature and then spun down at 2,900 × g for 30 minutes. One mL of the polar phase was dried down in a vacuum concentrator. Polar samples were derivatized by adding 120 μL of 15 mg mL-1 of methoxyamine HCl in pyridine, incubated at 50°C for 30 minutes and sonicated until all crystals disappeared. After that, 120 μL of MSTFA + 1% TMCS were added, incubated at 50°C for 30 minutes and immediately submitted for analysis with a Thermo Finnigan Polaris Q230 GC-MS (Thermo Electron Corporation, San Jose, CA, USA). The inlet and transfer lines were held at 240°C and 320°C, respectively. Separation was achieved with a temperature program of 80°C for 3 min, then ramped at 5°C min-1 to 315°C and held for 17 min, using a 60 m DB-5MS column (J&W Scientific, 0.25 mm ID, 0.25 μm film thickness) and a constant flow of 1.0 ml min-1. Derivatized samples (120 μL) were transferred to a 200 μL silanized vial insert and run at an injection split of 200:1 to bring the large peaks to a concentration within the range of the detector. Identity of all organic acids, sugars and amino acids were verified by comparison with standards purchased from Sigma-Aldrich (St. Louis, MO, USA).

Metabolite data processing

Metabolites were identified from the chromatograms using two different software packages: AMDIS (2.64, United States Department of Defense, USA) and Xcalibur (1.3; Thermo Electron Corporation). The software matched the mass spectrum in each peak against three different metabolite libraries: NIST ver. 2.0 library [126], T_MSRI_ID library of the Golm Metabolome Database [127] and our own custom-created UNR library (V1) made from more than 50 standards bought from Sigma-Aldrich. Quantification of the area of the chromatogram peaks was determined using Xcalibur and normalized as a ratio of the area of the peak of the ribitol internal standard.

Starch determination

Starch assays were performed according to Dubois et al. [128]; 100 mg of berry powder from E-L stages (35 to 38) were finely ground and incubated in 5 mL of methanol (80/20; v/v) at 80°C for 40 min. This step eliminates soluble sugars. The methanol extract was removed and the pellet was washed twice with distilled water. The remaining pellet was incubated overnight in 1.2 mL of acetate buffer (40 mM sodium acetate, 60 mM acetic acid) and 0.2 mL of enzymes solution (3 units of amyloglucosidase and 0.25 units of α-amylase); 0.5 mL of the supernatant was mixed with 0.5 mL of water and 1 mL of phenol (5/95; v/v). Thereafter, 5 mL of concentrated sulfuric acid was added and the solution was left to cool for 15 min. Glucose was measured by its absorbance at 483 nm and expressed in terms of μg of glucose per g fresh weight of berry sample. Calibration of the concentration of glucose was performed by determining the absorbance of several concentrations of glucose standards at 483 nm (0, 20, 40, 80, 120, 160, 200 μg ml-1).

Declarations

Acknowledgements

This work was supported by grants from the National Science Foundation (NSF) Plant Genome program (DBI-0217653) to G.R.C., J.C.C., and D.A.S. and the Bioinformatics program (DBI-0136561) to K.A.S. The Nevada Genomics and Proteomics Centers are supported by grants from the NIH Biomedical Research Infrastructure Network (NIH-NCRR, P20 RR16464) and NIH IDeA Network of Biomedical Research Excellence (INBRE, RR-03-008). This research was supported, in part, by the Nevada Agricultural Experiment Station, publication # 03077039. The authors are indebted to Rebecca Albion and Kitty Spreeman for their invaluable technical support. The authors would like to especially thank Leon Sobon of Sobon Estate and Shenandoah Vineyards, Amador County, California for allowing us to collect the berry samples used in this study.

Authors’ Affiliations

(1)
Department of Biochemistry and Molecular Biology, University of Nevada
(2)
Department of Animal Biotechnology, University of Nevada
(3)
Boston University School of Medicine, Department of Genetics and Genomics, Boston University, E632

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